# Buggy code
def fit(
    self,
    X,
    y,
    task=MULTICLASS_CLASSIFICATION,
    metric="acc_metric",
    feat_type=None,
    dataset_name=None,
):
    if not self._shared_mode:
        self._backend.context.delete_directories()
    else:
        # If this fails, it's likely that this is the first call to get
        # the data manager
        try:
            D = self._backend.load_datamanager()
            dataset_name = D.name
        except IOError:
            pass

    self._backend.context.create_directories()

    if dataset_name is None:
        m = hashlib.md5()
        m.update(X.data)
        dataset_name = m.hexdigest()

    self._backend.save_start_time(self._seed)
    self._stopwatch = StopWatch()
    self._dataset_name = dataset_name
    self._stopwatch.start_task(self._dataset_name)

    self._logger = self._get_logger(dataset_name)

    if isinstance(metric, str):
        metric = STRING_TO_METRIC[metric]

    if feat_type is not None and len(feat_type) != X.shape[1]:
        raise ValueError(
            "Array feat_type does not have same number of "
            "variables as X has features. %d vs %d." % (len(feat_type), X.shape[1])
        )
    if feat_type is not None and not all([isinstance(f, str) for f in feat_type]):
        raise ValueError("Array feat_type must only contain strings.")
    if feat_type is not None:
        for ft in feat_type:
            if ft.lower() not in ["categorical", "numerical"]:
                raise ValueError(
                    "Only `Categorical` and `Numerical` are "
                    "valid feature types, you passed `%s`" % ft
                )

    self._data_memory_limit = None
    loaded_data_manager = XYDataManager(
        X,
        y,
        task=task,
        metric=metric,
        feat_type=feat_type,
        dataset_name=dataset_name,
        encode_labels=False,
    )

    return self._fit(loaded_data_manager)


# Traceback (ValueError)
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Boiler plate\n",
    "import time\n",
    "from tqdm import *\n",
    "from tpot import TPOT\n",
    "import autosklearn.classification\n",
    "import sklearn.datasets\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.cross_validation import train_test_split\n",
    "\n",
    "#Set the random seed for reproducibility across computers\n",
    "vRndSeed = np.random.RandomState(seed=786196074)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>42</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>36</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    0  1  2   3  4  5  6  7  8  9\n",
       "0  24  2  3   3  1  1  2  3  0  1\n",
       "1  45  1  3  10  1  1  3  4  0  1\n",
       "2  43  2  3   7  1  1  3  4  0  1\n",
       "3  42  3  2   9  1  1  3  3  0  1\n",
       "4  36  3  3   8  1  1  3  2  0  1"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MLMe = pd.read_table(\"data/dtcmc.data.txt\", \",\", header=None)\n",
    "MLMe.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Factorize encodings if necessary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "MLMe.rename(columns={9 : 'class'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        int64\n",
       "1        int64\n",
       "2        int64\n",
       "3        int64\n",
       "4        int64\n",
       "5        int64\n",
       "6        int64\n",
       "7        int64\n",
       "8        int64\n",
       "class    int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MLMe.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        False\n",
       "1        False\n",
       "2        False\n",
       "3        False\n",
       "4        False\n",
       "5        False\n",
       "6        False\n",
       "7        False\n",
       "8        False\n",
       "class    False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.isnull(MLMe).any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Validate - need to fill out this section more\n",
    "MLMe_class = MLMe['class'].values\n",
    "assert (len(MLMe_class) == len(MLMe.index)), \"Not matching\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((1473, 10), (1473,))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MLMe.shape, MLMe_class.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1104, 369)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training_indices, validation_indices = training_indices, testing_indices = train_test_split(MLMe.index, stratify = MLMe_class, train_size=0.75, test_size=0.25)\n",
    "\n",
    "training_indices.size, validation_indices.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "X_train = np.ascontiguousarray(MLMe.drop('class',axis=1).loc[training_indices].values)\n",
    "y_train = np.ascontiguousarray(MLMe.loc[training_indices,'class'].values)\n",
    "\n",
    "X_test = np.ascontiguousarray(MLMe.drop('class',axis=1).loc[validation_indices].values)\n",
    "y_test = np.ascontiguousarray(MLMe.loc[validation_indices, 'class'].values)\n",
    "\n",
    "#X_train, y_train, X_test, y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((1104, 9), (1104,), (369, 9), (369,))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape, y_train.shape, X_test.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(dtype('int64'), dtype('int64'), dtype('int64'), dtype('int64'))"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.dtype, y_train.dtype, X_test.dtype, y_test.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(  C_CONTIGUOUS : True\n",
       "   F_CONTIGUOUS : False\n",
       "   OWNDATA : True\n",
       "   WRITEABLE : True\n",
       "   ALIGNED : True\n",
       "   UPDATEIFCOPY : False,   C_CONTIGUOUS : True\n",
       "   F_CONTIGUOUS : True\n",
       "   OWNDATA : True\n",
       "   WRITEABLE : True\n",
       "   ALIGNED : True\n",
       "   UPDATEIFCOPY : False,   C_CONTIGUOUS : True\n",
       "   F_CONTIGUOUS : False\n",
       "   OWNDATA : True\n",
       "   WRITEABLE : True\n",
       "   ALIGNED : True\n",
       "   UPDATEIFCOPY : False,   C_CONTIGUOUS : True\n",
       "   F_CONTIGUOUS : True\n",
       "   OWNDATA : True\n",
       "   WRITEABLE : True\n",
       "   ALIGNED : True\n",
       "   UPDATEIFCOPY : False)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.flags, y_train.flags, X_test.flags, y_test.flags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:   2%|▏         | 101/5200 [00:36<31:29,  2.70pipeline/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 1 - Current best internal CV score: 0.62016\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:   4%|▎         | 189/5200 [00:00<1:43:21,  1.24s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 2 - Current best internal CV score: 0.62450\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:   6%|▌         | 300/5200 [02:47<38:20,  2.13pipeline/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 3 - Current best internal CV score: 0.63011\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:   7%|▋         | 389/5200 [00:00<1:57:04,  1.46s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 4 - Current best internal CV score: 0.63136\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:   9%|▉         | 489/5200 [00:00<2:40:16,  2.04s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 5 - Current best internal CV score: 0.63415\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  11%|█▏        | 587/5200 [00:00<2:13:14,  1.73s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 6 - Current best internal CV score: 0.64038\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  13%|█▎        | 693/5200 [00:00<2:57:17,  2.36s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 7 - Current best internal CV score: 0.64038\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  15%|█▌        | 789/5200 [00:00<2:12:40,  1.80s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 8 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  17%|█▋        | 896/5200 [00:00<1:53:17,  1.58s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 9 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  19%|█▉        | 986/5200 [00:00<1:24:58,  1.21s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 10 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  21%|██        | 1087/5200 [00:00<1:47:46,  1.57s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 11 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  23%|██▎       | 1188/5200 [00:00<1:25:09,  1.27s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 12 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  25%|██▍       | 1292/5200 [00:00<1:26:51,  1.33s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 13 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  27%|██▋       | 1394/5200 [00:00<1:17:11,  1.22s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 14 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  29%|██▊       | 1484/5200 [00:00<56:53,  1.09pipeline/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 15 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  31%|███       | 1590/5200 [00:00<1:24:47,  1.41s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 16 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  33%|███▎      | 1692/5200 [00:00<1:16:58,  1.32s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 17 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  35%|███▍      | 1795/5200 [00:00<1:10:13,  1.24s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 18 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  36%|███▋      | 1888/5200 [00:00<1:18:50,  1.43s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 19 - Current best internal CV score: 0.64317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  38%|███▊      | 1990/5200 [00:00<1:12:59,  1.36s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 20 - Current best internal CV score: 0.64392\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  40%|████      | 2082/5200 [00:00<1:07:48,  1.30s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 21 - Current best internal CV score: 0.64392\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  42%|████▏     | 2193/5200 [00:00<1:13:34,  1.47s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 22 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  44%|████▍     | 2286/5200 [00:00<1:15:38,  1.56s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 23 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  46%|████▌     | 2393/5200 [00:00<1:06:45,  1.43s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 24 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  48%|████▊     | 2493/5200 [00:00<1:18:55,  1.75s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 25 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  50%|████▉     | 2586/5200 [00:00<52:42,  1.21s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 26 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  52%|█████▏    | 2688/5200 [00:00<1:40:47,  2.41s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 27 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  54%|█████▎    | 2789/5200 [00:00<53:18,  1.33s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 28 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  56%|█████▌    | 2889/5200 [00:00<1:06:12,  1.72s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 29 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  58%|█████▊    | 2991/5200 [00:00<1:25:08,  2.31s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 30 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  59%|█████▉    | 3091/5200 [00:00<44:32,  1.27s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 31 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  61%|██████▏   | 3188/5200 [00:00<38:43,  1.15s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 32 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  63%|██████▎   | 3293/5200 [00:00<33:04,  1.04s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 33 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  65%|██████▌   | 3393/5200 [00:00<34:03,  1.13s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 34 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  67%|██████▋   | 3487/5200 [00:00<51:12,  1.79s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 35 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  69%|██████▉   | 3600/5200 [1:14:42<1:10:39,  2.65s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 36 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  71%|███████   | 3690/5200 [00:00<31:57,  1.27s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 37 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  73%|███████▎  | 3788/5200 [00:00<33:18,  1.42s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 38 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  75%|███████▍  | 3890/5200 [00:00<34:09,  1.56s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 39 - Current best internal CV score: 0.64626\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  77%|███████▋  | 3995/5200 [00:00<38:16,  1.91s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 40 - Current best internal CV score: 0.64877\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  79%|███████▊  | 4086/5200 [00:00<36:41,  1.98s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 41 - Current best internal CV score: 0.64877\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  81%|████████  | 4194/5200 [00:00<24:16,  1.45s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 42 - Current best internal CV score: 0.64877\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  83%|████████▎ | 4294/5200 [00:00<20:33,  1.36s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 43 - Current best internal CV score: 0.64987\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  84%|████████▍ | 4392/5200 [00:00<23:18,  1.73s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 44 - Current best internal CV score: 0.64987\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  86%|████████▋ | 4486/5200 [00:00<16:45,  1.41s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 45 - Current best internal CV score: 0.64987\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  88%|████████▊ | 4590/5200 [00:00<14:30,  1.43s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 46 - Current best internal CV score: 0.64987\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  90%|█████████ | 4691/5200 [00:00<09:37,  1.14s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 47 - Current best internal CV score: 0.64987\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  92%|█████████▏| 4788/5200 [00:00<14:13,  2.07s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 48 - Current best internal CV score: 0.64987\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  94%|█████████▍| 4887/5200 [00:00<10:04,  1.93s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 49 - Current best internal CV score: 0.64987\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  96%|█████████▌| 4989/5200 [00:00<06:48,  1.94s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 50 - Current best internal CV score: 0.64987\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GP Progress:  98%|█████████▊| 5093/5200 [00:00<02:11,  1.23s/pipeline]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 51 - Current best internal CV score: 0.64987\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": []
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Best pipeline: _gradient_boosting(input_df, 0.51000000000000001, 9.0, 0.28000000000000003)\n"
     ]
    }
   ],
   "source": [
    "tpot = TPOT(generations=51, verbosity=2)\n",
    "tpot.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.62077627636352106"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpot.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tpot.export('tpot_contraceptive_pipeline.py')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:51:06,381:AutoML(1):7a3a10b65f5366b76f046add6da72a1c] Starting to create dummy predictions.\n",
      "[INFO] [2016-08-16 07:51:06,408:AutoML(1):7a3a10b65f5366b76f046add6da72a1c] Finished creating dummy prediction 1/2.\n",
      "[INFO] [2016-08-16 07:51:06,434:AutoML(1):7a3a10b65f5366b76f046add6da72a1c] Finished creating dummy prediction 2/2.\n",
      "[INFO] [2016-08-16 07:51:07,022:AutoML(1):7a3a10b65f5366b76f046add6da72a1c] Start Ensemble with 599.35sec time left\n",
      "[INFO] [2016-08-16 07:51:07,035:AutoML(1):7a3a10b65f5366b76f046add6da72a1c] Start SMAC with 599.34sec time left\n",
      "[INFO] [2016-08-16 07:51:07,070:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Training default configurations on a subset of 364/1104 data points.\n",
      "[INFO] [2016-08-16 07:51:07,079:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 3 on SUBSET with size 364 and time limit 180s.\n",
      "[INFO] [2016-08-16 07:51:07,081:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 1.0\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 1\n",
      "  classifier:random_forest:min_samples_split, Value: 2\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.01\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:51:07,137:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.139344 1: 0.139344 2: 0.139344 3: 0.139344 4: 0.139344 5: 0.139344 6: 0.139344 7: 0.139344 8: 0.139344 9: 0.139344 10: 0.139344 11: 0.139344 12: 0.139344 13: 0.139344 14: 0.139344 15: 0.139344 16: 0.139344 17: 0.139344 18: 0.139344 19: 0.139344 20: 0.139344 21: 0.139344 22: 0.139344 23: 0.139344 24: 0.139344 25: 0.139344 26: 0.139344 27: 0.139344 28: 0.139344 29: 0.139344 30: 0.139344 31: 0.139344 32: 0.139344 33: 0.139344 34: 0.139344 35: 0.139344 36: 0.139344 37: 0.139344 38: 0.139344 39: 0.139344 40: 0.139344 41: 0.139344 42: 0.139344 43: 0.139344 44: 0.139344 45: 0.139344 46: 0.139344 47: 0.139344 48: 0.139344 49: 0.139344\n",
      "\tMembers: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 1.  0.]\n",
      "\tIdentifiers: (1, 1)\n",
      "[INFO] [2016-08-16 07:51:07,145:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.139344\n",
      "[INFO] [2016-08-16 07:51:07,147:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.083450 seconds\n",
      "[INFO] [2016-08-16 07:51:07,152:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (2)!.\n",
      "[INFO] [2016-08-16 07:51:07,154:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (2)!\n",
      "[INFO] [2016-08-16 07:51:07,307:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 3. configuration on SUBSET. Duration 0.194043; loss 0.729508; status 1; additional run info: ;duration: 0.19404339790344238;num_run:00003 \n",
      "[INFO] [2016-08-16 07:51:07,309:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished SUBSET training sucessfully with ratio 0.330000\n",
      "[INFO] [2016-08-16 07:51:07,312:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 4 on SUBSET with size 364 and time limit 180s.\n",
      "[INFO] [2016-08-16 07:51:07,313:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 0.0001\n",
      "  classifier:sgd:average, Value: True\n",
      "  classifier:sgd:eta0, Value: 0.01\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: optimal\n",
      "  classifier:sgd:loss, Value: hinge\n",
      "  classifier:sgd:n_iter, Value: 5\n",
      "  classifier:sgd:penalty, Value: l2\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.1\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:51:07,356:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 4. configuration on SUBSET. Duration 0.014617; loss 0.836066; status 1; additional run info: ;duration: 0.014616966247558594;num_run:00004 \n",
      "[INFO] [2016-08-16 07:51:07,358:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished SUBSET training sucessfully with ratio 0.330000\n",
      "[INFO] [2016-08-16 07:51:07,360:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 5 on SUBSET with size 364 and time limit 180s.\n",
      "[INFO] [2016-08-16 07:51:07,361:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 1.0\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 5\n",
      "  classifier:extra_trees:min_samples_split, Value: 5\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.1\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 2.0\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:51:07,516:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 5. configuration on SUBSET. Duration 0.127089; loss 1.098361; status 1; additional run info: ;duration: 0.1270890235900879;num_run:00005 \n",
      "[INFO] [2016-08-16 07:51:07,518:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished SUBSET training sucessfully with ratio 0.330000\n",
      "[INFO] [2016-08-16 07:51:07,521:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 6 on SUBSET with size 364 and time limit 180s.\n",
      "[INFO] [2016-08-16 07:51:07,523:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gaussian_nb\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.1\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:51:07,562:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 6. configuration on SUBSET. Duration 0.012073; loss 0.766393; status 1; additional run info: ;duration: 0.012073278427124023;num_run:00006 \n",
      "[INFO] [2016-08-16 07:51:07,564:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished SUBSET training sucessfully with ratio 0.330000\n",
      "[INFO] [2016-08-16 07:51:07,567:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Metadata directory: /opt/conda/lib/python3.5/site-packages/autosklearn/metalearning/files/acc_metric_multiclass.classification_dense\n",
      "[INFO] [2016-08-16 07:51:07,935:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Start calculating metafeatures for 7a3a10b65f5366b76f046add6da72a1c\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/numpy/lib/nanfunctions.py:1136: RuntimeWarning: Degrees of freedom <= 0 for slice.\n",
      "  warnings.warn(\"Degrees of freedom <= 0 for slice.\", RuntimeWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/numpy/lib/nanfunctions.py:675: RuntimeWarning: Mean of empty slice\n",
      "  warnings.warn(\"Mean of empty slice\", RuntimeWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:51:07,951:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Calculating Metafeatures (categorical attributes) took  0.02\n",
      "[INFO] [2016-08-16 07:51:07,986:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Calculating Metafeatures (encoded attributes) took  0.02sec\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n",
      "  DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:51:08,099:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Time left for 7a3a10b65f5366b76f046add6da72a1c after finding initial configurations: 597.27sec\n",
      "[INFO] [2016-08-16 07:51:08,102:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Metafeatures for dataset 7a3a10b65f5366b76f046add6da72a1cuiaeo\n",
      "  PercentageOfFeaturesWithMissingValues: 0.0\n",
      "  RatioNominalToNumerical: 0.0\n",
      "  ClassProbabilityMin: 0.22644927536231885\n",
      "  SymbolsMin: 0\n",
      "  ClassProbabilitySTD: 0.0822864030378\n",
      "  NumberOfFeaturesWithMissingValues: 0.0\n",
      "  NumberOfMissingValues: 0.0\n",
      "  ClassEntropy: 1.53938532217\n",
      "  KurtosisSTD: 3.04541281443\n",
      "  ClassProbabilityMax: 0.4266304347826087\n",
      "  NumberOfCategoricalFeatures: 0\n",
      "  LogDatasetRatio: -4.8094706495\n",
      "  LogInverseDatasetRatio: 4.8094706495\n",
      "  DatasetRatio: 0.008152173913043478\n",
      "  NumberOfInstancesWithMissingValues: 0.0\n",
      "  KurtosisMax: 9.05175671504\n",
      "  InverseDatasetRatio: 122.66666666666667\n",
      "  SkewnessMax: 3.32441825212\n",
      "  SymbolsMax: 0\n",
      "  ClassProbabilityMean: 0.333333333333\n",
      "  NumberOfFeatures: 9.0\n",
      "  SkewnessMin: -1.94653713851\n",
      "  SkewnessMean: -0.132110704661\n",
      "  NumberOfNumericFeatures: 9\n",
      "  LogNumberOfFeatures: 2.19722457734\n",
      "  RatioNumericalToNominal: 0.0\n",
      "  NumberOfInstances: 1104.0\n",
      "  KurtosisMean: 1.01017630883\n",
      "  PercentageOfInstancesWithMissingValues: 0.0\n",
      "  LandmarkRandomNodeLearner: 0.417541827542\n",
      "  NumberOfClasses: 3.0\n",
      "  SymbolsSum: 0.0\n",
      "  SymbolsSTD: 0\n",
      "  LogNumberOfInstances: 7.00669522684\n",
      "  SkewnessSTD: 1.49178078579\n",
      "  SymbolsMean: 0\n",
      "  KurtosisMin: -1.33713825174\n",
      "  PercentageOfMissingValues: 0.0\n",
      "\n",
      "[INFO] [2016-08-16 07:51:08,107:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] ['1018_acc', '1128_acc', '871_acc', '1166_acc', '57_acc', '821_acc', '18_acc', '1067_acc', '300_acc', '966_acc', '720_acc', '293_acc', '395_acc', '1056_acc', '1021_acc', '743_acc', '734_acc', '273_acc', '23_acc', '1049_acc', '181_acc', '1142_acc', '816_acc', '843_acc', '26_acc', '903_acc', '179_acc', '807_acc', '977_acc', '1040_acc', '979_acc', '31_acc', '1112_acc', '185_acc', '1050_acc', '741_acc', '728_acc', '737_acc', '1053_acc', '1002_acc', '401_acc', '881_acc', '1068_acc', '930_acc', '1000_acc', '822_acc', '1139_acc', '182_acc', '393_acc', '357_acc', '554_acc', '28_acc', '819_acc', '722_acc', '1146_acc', '866_acc', '991_acc', '1130_acc', '959_acc', '735_acc', '1134_acc', '38_acc', '914_acc', '6_acc', '904_acc', '845_acc', '1161_acc', '799_acc', '718_acc', '727_acc', '913_acc', '396_acc', '723_acc', '797_acc', '772_acc', '3_acc', '1020_acc', '44_acc', '934_acc', '180_acc', '958_acc', '803_acc', '1120_acc', '354_acc', '14_acc', '16_acc', '60_acc', '1138_acc', '21_acc', '833_acc', '912_acc', '971_acc', '22_acc', '953_acc', '184_acc', '993_acc', '12_acc', '897_acc', '752_acc', '391_acc', '806_acc', '24_acc', '1116_acc', '980_acc', '392_acc', '976_acc', '978_acc', '1069_acc', '1114_acc', '679_acc', '30_acc', '46_acc', '1119_acc', '761_acc', '917_acc', '389_acc', '1041_acc', '846_acc', '390_acc', '995_acc', '751_acc', '847_acc', '398_acc', '351_acc', '813_acc', '849_acc', '837_acc', '399_acc', '962_acc', '36_acc', '1019_acc', '7a3a10b65f5366b76f046add6da72a1cuiaeo', '32_acc', '715_acc', '923_acc', '1036_acc', '1111_acc', '740_acc', '901_acc', '910_acc', '823_acc']\n",
      "[ERROR] [2016-08-16 07:51:09,164:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:51:09,350:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.270492 1: 0.270492 2: 0.270492 3: 0.270492 4: 0.270492 5: 0.270492 6: 0.270492 7: 0.270492 8: 0.270492 9: 0.270492 10: 0.270492 11: 0.270492 12: 0.270492 13: 0.270492 14: 0.270492 15: 0.270492 16: 0.270492 17: 0.270492 18: 0.270492 19: 0.270492 20: 0.270492 21: 0.270492 22: 0.270492 23: 0.270492 24: 0.270492 25: 0.270492 26: 0.270492 27: 0.270492 28: 0.270492 29: 0.270492 30: 0.270492 31: 0.270492 32: 0.270492 33: 0.270492 34: 0.270492 35: 0.270492 36: 0.270492 37: 0.270492 38: 0.270492 39: 0.270492 40: 0.270492 41: 0.270492 42: 0.270492 43: 0.270492 44: 0.270492 45: 0.270492 46: 0.270492 47: 0.270492 48: 0.270492 49: 0.270492\n",
      "\tMembers: [2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.98  0.    0.02  0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 3)\n",
      "[INFO] [2016-08-16 07:51:09,354:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.270492\n",
      "[INFO] [2016-08-16 07:51:09,356:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.195199 seconds\n",
      "[INFO] [2016-08-16 07:51:09,358:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (6)!.\n",
      "[INFO] [2016-08-16 07:51:09,360:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (6)!\n",
      "[INFO] [2016-08-16 07:51:44,407:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 7. configuration (default configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:44,410:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 1.0\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 1\n",
      "  classifier:random_forest:min_samples_split, Value: 2\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.01\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:51:44,633:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 7. configuration. Duration 0.185781; loss 0.725410; status 1; additional run info: ;duration: 0.18578052520751953;num_run:00007 \n",
      "[INFO] [2016-08-16 07:51:44,636:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 8. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:44,638:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.027813080646332755\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 3\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 11\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 100\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.2055753890049334\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.009992290843490832\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:51:44,758:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 8. configuration. Duration 0.092086; loss 0.696721; status 1; additional run info: ;duration: 0.0920858383178711;num_run:00008 \n",
      "[INFO] [2016-08-16 07:51:44,761:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 9. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:44,763:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 0.0005401543374603144\n",
      "  classifier:sgd:average, Value: False\n",
      "  classifier:sgd:eta0, Value: 0.04377140004056303\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: optimal\n",
      "  classifier:sgd:loss, Value: log\n",
      "  classifier:sgd:n_iter, Value: 943\n",
      "  classifier:sgd:penalty, Value: l2\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0007887810786977907\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.17377268248209546\n",
      "  preprocessor:select_rates:mode, Value: fwe\n",
      "  preprocessor:select_rates:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[ERROR] [2016-08-16 07:51:45,456:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:51:45,459:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 9. configuration. Duration 0.667637; loss 0.844262; status 1; additional run info: ;duration: 0.6676368713378906;num_run:00009 \n",
      "[INFO] [2016-08-16 07:51:45,461:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 10. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:45,463:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.05602526032246091\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 8\n",
      "  classifier:gradient_boosting:max_features, Value: 4.526821406542622\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 2\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 5\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 0.5698904089850234\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.014830428662911994\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.3041931851021964\n",
      "  preprocessor:select_rates:mode, Value: fpr\n",
      "  preprocessor:select_rates:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:51:45,722:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.303279 1: 0.327869 2: 0.327869 3: 0.327869 4: 0.327869 5: 0.327869 6: 0.327869 7: 0.327869 8: 0.327869 9: 0.327869 10: 0.327869 11: 0.327869 12: 0.327869 13: 0.327869 14: 0.327869 15: 0.327869 16: 0.327869 17: 0.327869 18: 0.327869 19: 0.327869 20: 0.327869 21: 0.327869 22: 0.327869 23: 0.327869 24: 0.327869 25: 0.327869 26: 0.327869 27: 0.327869 28: 0.327869 29: 0.327869 30: 0.327869 31: 0.327869 32: 0.327869 33: 0.327869 34: 0.327869 35: 0.327869 36: 0.327869 37: 0.327869 38: 0.327869 39: 0.327869 40: 0.327869 41: 0.327869 42: 0.327869 43: 0.327869 44: 0.327869 45: 0.327869 46: 0.327869 47: 0.327869 48: 0.327869 49: 0.327869\n",
      "\tMembers: [6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.96  0.    0.    0.    0.    0.    0.02  0.02]\n",
      "\tIdentifiers: (1, 1) (1, 8) (1, 9)\n",
      "[INFO] [2016-08-16 07:51:45,727:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.327869\n",
      "[INFO] [2016-08-16 07:51:45,728:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.275878 seconds\n",
      "[INFO] [2016-08-16 07:51:45,731:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (9)!.\n",
      "[INFO] [2016-08-16 07:51:45,732:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (9)!\n",
      "[INFO] [2016-08-16 07:51:46,850:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 10. configuration. Duration 1.343028; loss 0.713115; status 1; additional run info: ;duration: 1.3430280685424805;num_run:00010 \n",
      "[INFO] [2016-08-16 07:51:46,853:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 11. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:46,855:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.7129561445167657\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 5\n",
      "  classifier:gradient_boosting:max_features, Value: 3.93371407131337\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 20\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 4\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 0.5706975618082643\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.015787599946780754\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[ERROR] [2016-08-16 07:51:47,744:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:51:47,769:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 11. configuration. Duration 0.869216; loss 0.750000; status 1; additional run info: ;duration: 0.8692162036895752;num_run:00011 \n",
      "[INFO] [2016-08-16 07:51:47,772:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 12. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:47,774:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.20066795319926028\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 7\n",
      "  classifier:gradient_boosting:max_features, Value: 3.9325869489731167\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 7\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 11\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 0.9976532055747943\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00046199690730130277\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:51:48,105:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.303279 1: 0.327869 2: 0.327869 3: 0.327869 4: 0.327869 5: 0.327869 6: 0.327869 7: 0.327869 8: 0.327869 9: 0.327869 10: 0.327869 11: 0.327869 12: 0.327869 13: 0.327869 14: 0.327869 15: 0.327869 16: 0.327869 17: 0.327869 18: 0.327869 19: 0.327869 20: 0.327869 21: 0.327869 22: 0.327869 23: 0.327869 24: 0.327869 25: 0.327869 26: 0.327869 27: 0.327869 28: 0.327869 29: 0.327869 30: 0.327869 31: 0.327869 32: 0.327869 33: 0.327869 34: 0.327869 35: 0.327869 36: 0.327869 37: 0.327869 38: 0.327869 39: 0.327869 40: 0.327869 41: 0.327869 42: 0.327869 43: 0.327869 44: 0.327869 45: 0.327869 46: 0.327869 47: 0.327869 48: 0.327869 49: 0.327869\n",
      "\tMembers: [6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.96  0.    0.    0.    0.    0.    0.02  0.02  0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 8) (1, 9)\n",
      "[INFO] [2016-08-16 07:51:48,111:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.327869\n",
      "[INFO] [2016-08-16 07:51:48,113:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.372244 seconds\n",
      "[INFO] [2016-08-16 07:51:48,115:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:51:48,854:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 12. configuration. Duration 1.036347; loss 0.750000; status 1; additional run info: ;duration: 1.0363473892211914;num_run:00012 \n",
      "[INFO] [2016-08-16 07:51:48,857:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 13. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:48,859:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.07803133051910395\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 10\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 2\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 100\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.41767000017936246\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.006665191731327244\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:51:49,132:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 13. configuration. Duration 0.239706; loss 0.680328; status 1; additional run info: ;duration: 0.23970603942871094;num_run:00013 \n",
      "[INFO] [2016-08-16 07:51:49,135:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 14. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:49,136:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.320190941684566\n",
      "  classifier:adaboost:max_depth, Value: 3\n",
      "  classifier:adaboost:n_estimators, Value: 178\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:51:49,761:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 14. configuration. Duration 0.583321; loss 0.692623; status 1; additional run info: ;duration: 0.5833206176757812;num_run:00014 \n",
      "[INFO] [2016-08-16 07:51:49,764:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 15. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:49,767:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 3.2877276772399777\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 3\n",
      "  classifier:random_forest:min_samples_split, Value: 6\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0059197487245511455\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run3\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:51:50,127:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:51:50,145:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 15. configuration. Duration 0.342097; loss 0.721311; status 1; additional run info: ;duration: 0.34209728240966797;num_run:00015 \n",
      "[INFO] [2016-08-16 07:51:50,147:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 16. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:50,148:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 1.0081104516473922\n",
      "  classifier:adaboost:max_depth, Value: 6\n",
      "  classifier:adaboost:n_estimators, Value: 468\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: liblinear_svc_preprocessor\n",
      "  preprocessor:liblinear_svc_preprocessor:C, Value: 1.1828431725901418\n",
      "  preprocessor:liblinear_svc_preprocessor:dual, Constant: False\n",
      "  preprocessor:liblinear_svc_preprocessor:fit_intercept, Constant: True\n",
      "  preprocessor:liblinear_svc_preprocessor:intercept_scaling, Constant: 1\n",
      "  preprocessor:liblinear_svc_preprocessor:loss, Value: squared_hinge\n",
      "  preprocessor:liblinear_svc_preprocessor:multi_class, Constant: ovr\n",
      "  preprocessor:liblinear_svc_preprocessor:penalty, Constant: l1\n",
      "  preprocessor:liblinear_svc_preprocessor:tol, Value: 0.0022792606924326923\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:51:50,571:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.319672 1: 0.344262 2: 0.344262 3: 0.344262 4: 0.344262 5: 0.344262 6: 0.344262 7: 0.344262 8: 0.344262 9: 0.344262 10: 0.344262 11: 0.344262 12: 0.344262 13: 0.344262 14: 0.344262 15: 0.344262 16: 0.344262 17: 0.344262 18: 0.344262 19: 0.344262 20: 0.344262 21: 0.344262 22: 0.344262 23: 0.344262 24: 0.344262 25: 0.344262 26: 0.344262 27: 0.344262 28: 0.344262 29: 0.344262 30: 0.344262 31: 0.344262 32: 0.344262 33: 0.344262 34: 0.344262 35: 0.344262 36: 0.344262 37: 0.344262 38: 0.344262 39: 0.344262 40: 0.344262 41: 0.344262 42: 0.344262 43: 0.344262 44: 0.344262 45: 0.344262 46: 0.344262 47: 0.344262 48: 0.344262 49: 0.344262\n",
      "\tMembers: [11, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.96  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.02\n",
      "  0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 9) (1, 13)\n",
      "[INFO] [2016-08-16 07:51:50,576:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.344262\n",
      "[INFO] [2016-08-16 07:51:50,578:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.453958 seconds\n",
      "[INFO] [2016-08-16 07:51:50,580:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (14)!.\n",
      "[INFO] [2016-08-16 07:51:50,582:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (14)!\n",
      "[ERROR] [2016-08-16 07:51:50,589:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:51:51,128:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.319672 1: 0.344262 2: 0.344262 3: 0.344262 4: 0.344262 5: 0.344262 6: 0.344262 7: 0.344262 8: 0.344262 9: 0.344262 10: 0.344262 11: 0.344262 12: 0.344262 13: 0.344262 14: 0.344262 15: 0.344262 16: 0.344262 17: 0.344262 18: 0.344262 19: 0.344262 20: 0.344262 21: 0.344262 22: 0.344262 23: 0.344262 24: 0.344262 25: 0.344262 26: 0.344262 27: 0.344262 28: 0.344262 29: 0.344262 30: 0.344262 31: 0.344262 32: 0.344262 33: 0.344262 34: 0.344262 35: 0.344262 36: 0.344262 37: 0.344262 38: 0.344262 39: 0.344262 40: 0.344262 41: 0.344262 42: 0.344262 43: 0.344262 44: 0.344262 45: 0.344262 46: 0.344262 47: 0.344262 48: 0.344262 49: 0.344262\n",
      "\tMembers: [11, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.96  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.02\n",
      "  0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 9) (1, 13)\n",
      "[INFO] [2016-08-16 07:51:51,132:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.344262\n",
      "[INFO] [2016-08-16 07:51:51,133:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.548280 seconds\n",
      "[INFO] [2016-08-16 07:51:51,135:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:51:51,160:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 16. configuration. Duration 0.955629; loss 0.786885; status 1; additional run info: ;duration: 0.9556291103363037;num_run:00016 \n",
      "[INFO] [2016-08-16 07:51:51,163:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 17. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:51,164:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: liblinear_svc\n",
      "  classifier:liblinear_svc:C, Value: 16.445846112636396\n",
      "  classifier:liblinear_svc:dual, Constant: False\n",
      "  classifier:liblinear_svc:fit_intercept, Constant: True\n",
      "  classifier:liblinear_svc:intercept_scaling, Constant: 1\n",
      "  classifier:liblinear_svc:loss, Value: squared_hinge\n",
      "  classifier:liblinear_svc:multi_class, Constant: ovr\n",
      "  classifier:liblinear_svc:penalty, Value: l2\n",
      "  classifier:liblinear_svc:tol, Value: 5.031987397253124e-05\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.018681895366958703\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: nystroem_sampler\n",
      "  preprocessor:nystroem_sampler:gamma, Value: 0.2781157712712954\n",
      "  preprocessor:nystroem_sampler:kernel, Value: rbf\n",
      "  preprocessor:nystroem_sampler:n_components, Value: 8238\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/kernel_approximation.py:463: UserWarning: n_components > n_samples. This is not possible.\n",
      "n_components was set to n_samples, which results in inefficient evaluation of the full kernel.\n",
      "  warnings.warn(\"n_components > n_samples. This is not possible.\\n\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:51:52,795:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 17. configuration. Duration 1.530154; loss 0.766393; status 1; additional run info: ;duration: 1.5301539897918701;num_run:00017 \n",
      "[INFO] [2016-08-16 07:51:52,799:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 18. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:52,801:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 0.0018057707469332856\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: squared_hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 572\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.17556429026221484\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: nystroem_sampler\n",
      "  preprocessor:nystroem_sampler:gamma, Value: 0.35884375549922065\n",
      "  preprocessor:nystroem_sampler:kernel, Value: rbf\n",
      "  preprocessor:nystroem_sampler:n_components, Value: 481\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:51:53,158:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:51:53,702:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.319672 1: 0.344262 2: 0.344262 3: 0.344262 4: 0.344262 5: 0.344262 6: 0.344262 7: 0.344262 8: 0.344262 9: 0.344262 10: 0.344262 11: 0.344262 12: 0.344262 13: 0.344262 14: 0.344262 15: 0.344262 16: 0.344262 17: 0.344262 18: 0.344262 19: 0.344262 20: 0.344262 21: 0.344262 22: 0.344262 23: 0.344262 24: 0.344262 25: 0.344262 26: 0.344262 27: 0.344262 28: 0.344262 29: 0.344262 30: 0.344262 31: 0.344262 32: 0.344262 33: 0.344262 34: 0.344262 35: 0.344262 36: 0.344262 37: 0.344262 38: 0.344262 39: 0.344262 40: 0.344262 41: 0.344262 42: 0.344262 43: 0.344262 44: 0.344262 45: 0.344262 46: 0.344262 47: 0.344262 48: 0.344262 49: 0.344262\n",
      "\tMembers: [11, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.96  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.02\n",
      "  0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 9) (1, 13)\n",
      "[INFO] [2016-08-16 07:51:53,706:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.344262\n",
      "[INFO] [2016-08-16 07:51:53,708:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.561095 seconds\n",
      "[INFO] [2016-08-16 07:51:53,711:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:51:55,878:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 18. configuration. Duration 3.016266; loss 0.782787; status 1; additional run info: ;duration: 3.016265869140625;num_run:00018 \n",
      "[INFO] [2016-08-16 07:51:55,881:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 19. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:55,883:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.11209822960801213\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 3\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 14\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 100\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.6277896866125797\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.1847798648480348\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:51:56,032:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 19. configuration. Duration 0.114962; loss 0.688525; status 1; additional run info: ;duration: 0.11496233940124512;num_run:00019 \n",
      "[INFO] [2016-08-16 07:51:56,034:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 20. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:51:56,036:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 0.0036975653885940544\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 326\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 0.6227804363658538\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 1821\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:51:57,729:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:51:58,388:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.319672 1: 0.344262 2: 0.344262 3: 0.344262 4: 0.344262 5: 0.344262 6: 0.344262 7: 0.344262 8: 0.344262 9: 0.344262 10: 0.344262 11: 0.344262 12: 0.344262 13: 0.344262 14: 0.344262 15: 0.344262 16: 0.344262 17: 0.344262 18: 0.344262 19: 0.344262 20: 0.344262 21: 0.344262 22: 0.344262 23: 0.344262 24: 0.344262 25: 0.344262 26: 0.344262 27: 0.344262 28: 0.344262 29: 0.344262 30: 0.344262 31: 0.344262 32: 0.344262 33: 0.344262 34: 0.344262 35: 0.344262 36: 0.344262 37: 0.344262 38: 0.344262 39: 0.344262 40: 0.344262 41: 0.344262 42: 0.344262 43: 0.344262 44: 0.344262 45: 0.344262 46: 0.344262 47: 0.344262 48: 0.344262 49: 0.344262\n",
      "\tMembers: [11, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.96  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.02\n",
      "  0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 9) (1, 13)\n",
      "[INFO] [2016-08-16 07:51:58,393:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.344262\n",
      "[INFO] [2016-08-16 07:51:58,395:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.670073 seconds\n",
      "[INFO] [2016-08-16 07:51:58,396:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:52:01,067:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 20. configuration. Duration 4.962999; loss 0.790984; status 1; additional run info: ;duration: 4.962998867034912;num_run:00020 \n",
      "[INFO] [2016-08-16 07:52:01,070:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 21. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:01,072:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.4120597789233855\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 4.758121621535983\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 16\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 6\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 0.9698657674324143\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.45394720185957155\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: gini\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 2.9979113303712377\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 5\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 17\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:01,773:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 21. configuration. Duration 0.646324; loss 0.668033; status 1; additional run info: ;duration: 0.6463239192962646;num_run:00021 \n",
      "[INFO] [2016-08-16 07:52:01,775:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 22. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:01,776:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: qda\n",
      "  classifier:qda:reg_param, Value: 9.284928341343884\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.15973168347756866\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 1.0504384005484382\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 235\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/discriminant_analysis.py:688: UserWarning: Variables are collinear\n",
      "  warnings.warn(\"Variables are collinear\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:02,011:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 22. configuration. Duration 0.173836; loss 0.831967; status 1; additional run info: ;duration: 0.17383575439453125;num_run:00022 \n",
      "[INFO] [2016-08-16 07:52:02,014:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 23. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:02,016:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: liblinear_svc\n",
      "  classifier:liblinear_svc:C, Value: 62.21750028494345\n",
      "  classifier:liblinear_svc:dual, Constant: False\n",
      "  classifier:liblinear_svc:fit_intercept, Constant: True\n",
      "  classifier:liblinear_svc:intercept_scaling, Constant: 1\n",
      "  classifier:liblinear_svc:loss, Value: squared_hinge\n",
      "  classifier:liblinear_svc:multi_class, Constant: ovr\n",
      "  classifier:liblinear_svc:penalty, Value: l2\n",
      "  classifier:liblinear_svc:tol, Value: 0.0002178180133457927\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.028777961041830738\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "You are already timing task: index_run4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:52:02,415:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:02,756:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 23. configuration. Duration 0.708847; loss 0.717213; status 1; additional run info: ;duration: 0.7088468074798584;num_run:00023 \n",
      "[INFO] [2016-08-16 07:52:02,759:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 24. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:02,761:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 1.0\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 1\n",
      "  classifier:extra_trees:min_samples_split, Value: 2\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: gini\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 1.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 1\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 2\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:03,174:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.331967 1: 0.348361 2: 0.372951 3: 0.372951 4: 0.372951 5: 0.372951 6: 0.372951 7: 0.372951 8: 0.372951 9: 0.372951 10: 0.372951 11: 0.372951 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.372951 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [19, 17, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.94  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.02  0.    0.02  0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 9) (1, 19) (1, 21)\n",
      "[INFO] [2016-08-16 07:52:03,179:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:52:03,181:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.769840 seconds\n",
      "[INFO] [2016-08-16 07:52:03,184:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (22)!.\n",
      "[INFO] [2016-08-16 07:52:03,186:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (22)!\n",
      "[INFO] [2016-08-16 07:52:03,188:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 24. configuration. Duration 0.368447; loss 0.819672; status 1; additional run info: ;duration: 0.36844706535339355;num_run:00024 \n",
      "[INFO] [2016-08-16 07:52:03,190:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 25. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:03,192:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.08921861937738111\n",
      "  classifier:adaboost:max_depth, Value: 8\n",
      "  classifier:adaboost:n_estimators, Value: 473\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.46025920786341173\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[ERROR] [2016-08-16 07:52:03,194:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:04,139:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.331967 1: 0.348361 2: 0.372951 3: 0.372951 4: 0.372951 5: 0.372951 6: 0.372951 7: 0.372951 8: 0.372951 9: 0.372951 10: 0.372951 11: 0.372951 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.372951 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [19, 17, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.94  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.02  0.    0.02  0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 9) (1, 19) (1, 21)\n",
      "[INFO] [2016-08-16 07:52:04,146:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:52:04,148:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.958292 seconds\n",
      "[INFO] [2016-08-16 07:52:04,150:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:52:07,532:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 25. configuration. Duration 4.270654; loss 0.758197; status 1; additional run info: ;duration: 4.270654201507568;num_run:00025 \n",
      "[INFO] [2016-08-16 07:52:07,534:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 26. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:07,536:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.20883213948290555\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 5\n",
      "  classifier:gradient_boosting:max_features, Value: 3.950232147023257\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 2\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 12\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 0.7000722592104036\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.20504937335658277\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:52:08,175:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:08,396:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 26. configuration. Duration 0.814675; loss 0.725410; status 1; additional run info: ;duration: 0.8146753311157227;num_run:00026 \n",
      "[INFO] [2016-08-16 07:52:08,399:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 27. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:08,401:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 242\n",
      "  classifier:lda:shrinkage, Value: None\n",
      "  classifier:lda:tol, Value: 0.0011339574479631279\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.004889144803037605\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 8\n",
      "  preprocessor:gem:precond, Value: 0.39344596751061517\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/discriminant_analysis.py:387: UserWarning: Variables are collinear.\n",
      "  warnings.warn(\"Variables are collinear.\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:08,526:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 27. configuration. Duration 0.082217; loss 0.758197; status 1; additional run info: ;duration: 0.08221697807312012;num_run:00027 \n",
      "[INFO] [2016-08-16 07:52:08,528:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 28. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:08,530:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.09705831458471066\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 7\n",
      "  classifier:gradient_boosting:max_features, Value: 4.283409813794932\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 16\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 4\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 0.9843077531242675\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.1149368954241468\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: liblinear_svc_preprocessor\n",
      "  preprocessor:liblinear_svc_preprocessor:C, Value: 11920.402652363826\n",
      "  preprocessor:liblinear_svc_preprocessor:dual, Constant: False\n",
      "  preprocessor:liblinear_svc_preprocessor:fit_intercept, Constant: True\n",
      "  preprocessor:liblinear_svc_preprocessor:intercept_scaling, Constant: 1\n",
      "  preprocessor:liblinear_svc_preprocessor:loss, Value: squared_hinge\n",
      "  preprocessor:liblinear_svc_preprocessor:multi_class, Constant: ovr\n",
      "  preprocessor:liblinear_svc_preprocessor:penalty, Constant: l1\n",
      "  preprocessor:liblinear_svc_preprocessor:tol, Value: 0.0001606219620686348\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:09,088:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.331967 1: 0.348361 2: 0.372951 3: 0.372951 4: 0.372951 5: 0.372951 6: 0.372951 7: 0.372951 8: 0.372951 9: 0.372951 10: 0.372951 11: 0.372951 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.372951 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [19, 17, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.94  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.02  0.    0.02  0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 9) (1, 19) (1, 21)\n",
      "[INFO] [2016-08-16 07:52:09,095:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:52:09,098:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 0.926688 seconds\n",
      "[INFO] [2016-08-16 07:52:09,099:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:09,573:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 28. configuration. Duration 0.994685; loss 0.692623; status 1; additional run info: ;duration: 0.9946849346160889;num_run:00028 \n",
      "[INFO] [2016-08-16 07:52:09,575:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 29. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:09,576:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 295.4185183083245\n",
      "  classifier:libsvm_svc:gamma, Value: 0.05098015552849704\n",
      "  classifier:libsvm_svc:kernel, Value: rbf\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: False\n",
      "  classifier:libsvm_svc:tol, Value: 0.01616175671031427\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: cosine\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 216\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: mean\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:09,760:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 29. configuration. Duration 0.153612; loss 0.799180; status 1; additional run info: ;duration: 0.1536116600036621;num_run:00029 \n",
      "[INFO] [2016-08-16 07:52:09,762:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 30. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:09,764:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.10595850641686415\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 6\n",
      "  classifier:gradient_boosting:max_features, Value: 4.073047765066454\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 14\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 0.3730003562382372\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0007311404576904489\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: True\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 1.7764018125840484\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 4\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 4\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:10,817:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 30. configuration. Duration 0.999384; loss 0.692623; status 1; additional run info: ;duration: 0.9993844032287598;num_run:00030 \n",
      "[INFO] [2016-08-16 07:52:10,819:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 31. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:10,820:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: True\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 2.714684194470519\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 1\n",
      "  classifier:extra_trees:min_samples_split, Value: 9\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.17960116136139503\n",
      "  preprocessor:select_rates:mode, Value: fwe\n",
      "  preprocessor:select_rates:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:11,048:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 31. configuration. Duration 0.188849; loss 0.684426; status 1; additional run info: ;duration: 0.18884897232055664;num_run:00031 \n",
      "[INFO] [2016-08-16 07:52:11,050:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 32. configuration (meta-learning configuration) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:11,052:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: True\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 2.3779010566365115\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 2\n",
      "  classifier:extra_trees:min_samples_split, Value: 4\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.004305770290473698\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.30934089491790895\n",
      "  preprocessor:select_rates:mode, Value: fdr\n",
      "  preprocessor:select_rates:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:52:11,111:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:11,273:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 32. configuration. Duration 0.179694; loss 0.717213; status 1; additional run info: ;duration: 0.17969441413879395;num_run:00032 \n",
      "[INFO] [2016-08-16 07:52:11,331:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 26 training points for SMAC.\n",
      "[INFO] [2016-08-16 07:52:12,245:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.331967 1: 0.352459 2: 0.364754 3: 0.364754 4: 0.364754 5: 0.364754 6: 0.364754 7: 0.364754 8: 0.364754 9: 0.364754 10: 0.364754 11: 0.364754 12: 0.364754 13: 0.364754 14: 0.364754 15: 0.364754 16: 0.364754 17: 0.364754 18: 0.364754 19: 0.364754 20: 0.364754 21: 0.364754 22: 0.364754 23: 0.364754 24: 0.364754 25: 0.364754 26: 0.364754 27: 0.364754 28: 0.364754 29: 0.364754 30: 0.364754 31: 0.364754 32: 0.364754 33: 0.364754 34: 0.364754 35: 0.364754 36: 0.364754 37: 0.364754 38: 0.364754 39: 0.364754 40: 0.364754 41: 0.364754 42: 0.364754 43: 0.364754 44: 0.364754 45: 0.364754 46: 0.364754 47: 0.364754 48: 0.364754 49: 0.364754\n",
      "\tMembers: [19, 29, 25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.94  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.02]\n",
      "\tIdentifiers: (1, 1) (1, 21) (1, 27) (1, 31)\n",
      "[INFO] [2016-08-16 07:52:12,250:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.364754\n",
      "[INFO] [2016-08-16 07:52:12,251:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.144620 seconds\n",
      "[INFO] [2016-08-16 07:52:12,254:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (31)!.\n",
      "[INFO] [2016-08-16 07:52:12,255:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (31)!\n",
      "[ERROR] [2016-08-16 07:52:12,262:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:13,454:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.331967 1: 0.352459 2: 0.364754 3: 0.364754 4: 0.364754 5: 0.364754 6: 0.364754 7: 0.364754 8: 0.364754 9: 0.364754 10: 0.364754 11: 0.364754 12: 0.364754 13: 0.364754 14: 0.364754 15: 0.364754 16: 0.364754 17: 0.364754 18: 0.364754 19: 0.364754 20: 0.364754 21: 0.364754 22: 0.364754 23: 0.364754 24: 0.364754 25: 0.364754 26: 0.364754 27: 0.364754 28: 0.364754 29: 0.364754 30: 0.364754 31: 0.364754 32: 0.364754 33: 0.364754 34: 0.364754 35: 0.364754 36: 0.364754 37: 0.364754 38: 0.364754 39: 0.364754 40: 0.364754 41: 0.364754 42: 0.364754 43: 0.364754 44: 0.364754 45: 0.364754 46: 0.364754 47: 0.364754 48: 0.364754 49: 0.364754\n",
      "\tMembers: [19, 29, 25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.94  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.02  0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 21) (1, 27) (1, 31)\n",
      "[INFO] [2016-08-16 07:52:13,459:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.364754\n",
      "[INFO] [2016-08-16 07:52:13,460:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.202093 seconds\n",
      "[INFO] [2016-08-16 07:52:13,462:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:52:20,702:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 9.36969 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:52:20,708:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 33. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:20,709:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.412059778923\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 4.75812162154\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 16\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 6\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 0.969865767432\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.45394720186\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.1\n",
      "  preprocessor:select_rates:mode, Value: fpr\n",
      "  preprocessor:select_rates:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:21,271:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 33. configuration. Duration: 0.517077; loss: 0.852459; status 1; additional run info: ;duration: 0.5170767307281494;num_run:00033 \n",
      "[INFO] [2016-08-16 07:52:21,278:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 34. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:21,279:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 2.33621210907\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 5\n",
      "  classifier:random_forest:min_samples_split, Value: 5\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.0252216048729\n",
      "  preprocessor:select_rates:mode, Value: fpr\n",
      "  preprocessor:select_rates:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run6\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:52:21,488:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:21,854:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 34. configuration. Duration: 0.528580; loss: 0.688525; status 1; additional run info: ;duration: 0.5285797119140625;num_run:00034 \n",
      "[INFO] [2016-08-16 07:52:21,863:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 35. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:21,865:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.115184186584\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 5\n",
      "  classifier:gradient_boosting:max_features, Value: 2.96707210199\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 7\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 17\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 340\n",
      "  classifier:gradient_boosting:subsample, Value: 0.212660691858\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00983236043669\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:22,708:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.331967 1: 0.352459 2: 0.364754 3: 0.364754 4: 0.364754 5: 0.364754 6: 0.364754 7: 0.364754 8: 0.364754 9: 0.364754 10: 0.364754 11: 0.364754 12: 0.364754 13: 0.364754 14: 0.364754 15: 0.364754 16: 0.364754 17: 0.364754 18: 0.364754 19: 0.364754 20: 0.364754 21: 0.364754 22: 0.364754 23: 0.364754 24: 0.364754 25: 0.364754 26: 0.364754 27: 0.364754 28: 0.364754 29: 0.364754 30: 0.364754 31: 0.364754 32: 0.364754 33: 0.364754 34: 0.364754 35: 0.364754 36: 0.364754 37: 0.364754 38: 0.364754 39: 0.364754 40: 0.364754 41: 0.364754 42: 0.364754 43: 0.364754 44: 0.364754 45: 0.364754 46: 0.364754 47: 0.364754 48: 0.364754 49: 0.364754\n",
      "\tMembers: [19, 29, 25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.94  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.02  0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 21) (1, 27) (1, 31)\n",
      "[INFO] [2016-08-16 07:52:22,719:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.364754\n",
      "[INFO] [2016-08-16 07:52:22,724:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.239119 seconds\n",
      "[INFO] [2016-08-16 07:52:22,726:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run6\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:52:24,739:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:25,919:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.331967 1: 0.352459 2: 0.364754 3: 0.364754 4: 0.364754 5: 0.364754 6: 0.364754 7: 0.364754 8: 0.364754 9: 0.364754 10: 0.364754 11: 0.364754 12: 0.364754 13: 0.364754 14: 0.364754 15: 0.364754 16: 0.364754 17: 0.364754 18: 0.364754 19: 0.364754 20: 0.364754 21: 0.364754 22: 0.364754 23: 0.364754 24: 0.364754 25: 0.364754 26: 0.364754 27: 0.364754 28: 0.364754 29: 0.364754 30: 0.364754 31: 0.364754 32: 0.364754 33: 0.364754 34: 0.364754 35: 0.364754 36: 0.364754 37: 0.364754 38: 0.364754 39: 0.364754 40: 0.364754 41: 0.364754 42: 0.364754 43: 0.364754 44: 0.364754 45: 0.364754 46: 0.364754 47: 0.364754 48: 0.364754 49: 0.364754\n",
      "\tMembers: [19, 29, 25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.94  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.02  0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 21) (1, 27) (1, 31)\n",
      "[INFO] [2016-08-16 07:52:25,927:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.364754\n",
      "[INFO] [2016-08-16 07:52:25,928:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.193334 seconds\n",
      "[INFO] [2016-08-16 07:52:25,930:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:52:27,825:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 35. configuration. Duration: 5.889068; loss: 0.774590; status 1; additional run info: ;duration: 5.889067888259888;num_run:00035 \n",
      "[INFO] [2016-08-16 07:52:27,832:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 36. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:27,833:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.041226567609\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 8\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 1\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 363\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.703839251742\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: manhattan\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 17\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: mean\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run6\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:52:27,943:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:28,773:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 36. configuration. Duration: 0.905270; loss: 0.737705; status 1; additional run info: ;duration: 0.9052698612213135;num_run:00036 \n",
      "[INFO] [2016-08-16 07:52:28,780:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 37. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:28,782:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.101770112695\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:29,137:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.331967 1: 0.352459 2: 0.364754 3: 0.364754 4: 0.364754 5: 0.364754 6: 0.364754 7: 0.364754 8: 0.364754 9: 0.364754 10: 0.364754 11: 0.364754 12: 0.364754 13: 0.364754 14: 0.364754 15: 0.364754 16: 0.364754 17: 0.364754 18: 0.364754 19: 0.364754 20: 0.364754 21: 0.364754 22: 0.364754 23: 0.364754 24: 0.364754 25: 0.364754 26: 0.364754 27: 0.364754 28: 0.364754 29: 0.364754 30: 0.364754 31: 0.364754 32: 0.364754 33: 0.364754 34: 0.364754 35: 0.364754 36: 0.364754 37: 0.364754 38: 0.364754 39: 0.364754 40: 0.364754 41: 0.364754 42: 0.364754 43: 0.364754 44: 0.364754 45: 0.364754 46: 0.364754 47: 0.364754 48: 0.364754 49: 0.364754\n",
      "\tMembers: [19, 29, 25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.94  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.02  0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 21) (1, 27) (1, 31)\n",
      "[INFO] [2016-08-16 07:52:29,145:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.364754\n",
      "[INFO] [2016-08-16 07:52:29,148:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.208505 seconds\n",
      "[INFO] [2016-08-16 07:52:29,151:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:52:29,367:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 37. configuration. Duration: 0.539897; loss: 0.672131; status 1; additional run info: ;duration: 0.5398967266082764;num_run:00037 \n",
      "[INFO] [2016-08-16 07:52:29,374:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 38. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:29,376:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: entropy\n",
      "  classifier:decision_tree:max_depth, Value: 0.743842913028\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 10\n",
      "  classifier:decision_tree:min_samples_split, Value: 5\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:29,529:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 38. configuration. Duration: 0.124468; loss: 0.823770; status 1; additional run info: ;duration: 0.12446784973144531;num_run:00038 \n",
      "[INFO] [2016-08-16 07:52:29,535:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 39. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:29,537:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 5\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0111357313386\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:30,044:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 39. configuration. Duration: 0.463418; loss: 0.668033; status 1; additional run info: ;duration: 0.46341848373413086;num_run:00039 \n",
      "[INFO] [2016-08-16 07:52:30,050:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 40. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:30,051:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.0516850893531\n",
      "  classifier:adaboost:max_depth, Value: 1\n",
      "  classifier:adaboost:n_estimators, Value: 220\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 57.5873515211\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:52:30,399:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 40. configuration. Duration: 0.305610; loss: 0.663934; status 1; additional run info: ;duration: 0.30560970306396484;num_run:00040 \n",
      "[INFO] [2016-08-16 07:52:30,463:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 34 training points for SMAC.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run6\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:52:31,165:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:32,628:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.336066 1: 0.356557 2: 0.368852 3: 0.372951 4: 0.372951 5: 0.372951 6: 0.372951 7: 0.372951 8: 0.372951 9: 0.372951 10: 0.372951 11: 0.372951 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.372951 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [38, 12, 12, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.92  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02]\n",
      "\tIdentifiers: (1, 1) (1, 14) (1, 40)\n",
      "[INFO] [2016-08-16 07:52:32,634:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:52:32,636:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.474932 seconds\n",
      "[INFO] [2016-08-16 07:52:32,639:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (40)!.\n",
      "[INFO] [2016-08-16 07:52:32,641:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (40)!\n",
      "[INFO] [2016-08-16 07:52:42,285:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 11.821 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:52:42,290:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 41. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:42,292:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0137961211181\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:42,801:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 41. configuration. Duration: 0.466165; loss: 0.688525; status 1; additional run info: ;duration: 0.46616458892822266;num_run:00041 \n",
      "[INFO] [2016-08-16 07:52:42,807:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 42. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:42,808:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 4.61536913393e-05\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: squared_hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 101\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00067138318249\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: cube\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 116, in _ica_par\n",
      "    warnings.warn('FastICA did not converge. Consider increasing '\n",
      "UserWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:44,030:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 42. configuration. Duration: 1.216230; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:52:44,037:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 43. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:44,039:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 3\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 1\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 100\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:44,152:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 43. configuration. Duration: 0.086444; loss: 0.684426; status 1; additional run info: ;duration: 0.08644366264343262;num_run:00043 \n",
      "[INFO] [2016-08-16 07:52:44,157:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 44. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:44,159:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: gini\n",
      "  classifier:decision_tree:max_depth, Value: 1.94593017712\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 18\n",
      "  classifier:decision_tree:min_samples_split, Value: 2\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: gini\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 3.12809311606\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 2\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 16\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:44,352:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 44. configuration. Duration: 0.158649; loss: 0.741803; status 1; additional run info: ;duration: 0.15864944458007812;num_run:00044 \n",
      "[INFO] [2016-08-16 07:52:44,357:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 45. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:44,359:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 1.0\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 1\n",
      "  classifier:extra_trees:min_samples_split, Value: 2\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:44,586:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 45. configuration. Duration: 0.184005; loss: 0.750000; status 1; additional run info: ;duration: 0.184004545211792;num_run:00045 \n",
      "[INFO] [2016-08-16 07:52:44,592:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 46. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:44,593:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 110\n",
      "  classifier:lda:shrinkage, Value: None\n",
      "  classifier:lda:tol, Value: 0.0133662241448\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.415603644849\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: cube\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[ERROR] [2016-08-16 07:52:44,681:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 116, in _ica_par\n",
      "    warnings.warn('FastICA did not converge. Consider increasing '\n",
      "UserWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:45,863:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 46. configuration. Duration: 1.265523; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:52:45,869:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 47. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:45,882:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 1.0\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 1\n",
      "  classifier:extra_trees:min_samples_split, Value: 2\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:46,159:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 47. configuration. Duration: 0.230003; loss: 0.750000; status 1; additional run info: ;duration: 0.23000264167785645;num_run:00047 \n",
      "[INFO] [2016-08-16 07:52:46,166:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 48. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:46,168:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 0.000472573449469\n",
      "  classifier:sgd:average, Value: True\n",
      "  classifier:sgd:eta0, Value: 0.0582594738491\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: optimal\n",
      "  classifier:sgd:loss, Value: squared_hinge\n",
      "  classifier:sgd:n_iter, Value: 413\n",
      "  classifier:sgd:penalty, Value: l2\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.392993679011\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: liblinear_svc_preprocessor\n",
      "  preprocessor:liblinear_svc_preprocessor:C, Value: 1581.49831115\n",
      "  preprocessor:liblinear_svc_preprocessor:dual, Constant: False\n",
      "  preprocessor:liblinear_svc_preprocessor:fit_intercept, Constant: True\n",
      "  preprocessor:liblinear_svc_preprocessor:intercept_scaling, Constant: 1\n",
      "  preprocessor:liblinear_svc_preprocessor:loss, Value: squared_hinge\n",
      "  preprocessor:liblinear_svc_preprocessor:multi_class, Constant: ovr\n",
      "  preprocessor:liblinear_svc_preprocessor:penalty, Constant: l1\n",
      "  preprocessor:liblinear_svc_preprocessor:tol, Value: 0.00427826080249\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:46,192:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.336066 1: 0.356557 2: 0.368852 3: 0.372951 4: 0.372951 5: 0.372951 6: 0.372951 7: 0.372951 8: 0.372951 9: 0.372951 10: 0.372951 11: 0.372951 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.372951 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [38, 12, 12, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.92  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 14) (1, 40)\n",
      "[INFO] [2016-08-16 07:52:46,197:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:52:46,199:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.525202 seconds\n",
      "[INFO] [2016-08-16 07:52:46,200:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:46,547:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 48. configuration. Duration: 0.351487; loss: 0.795082; status 1; additional run info: ;duration: 0.3514871597290039;num_run:00048 \n",
      "[INFO] [2016-08-16 07:52:46,553:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 49. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:46,554:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 3\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 1\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 100\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:46,670:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 49. configuration. Duration: 0.089138; loss: 0.684426; status 1; additional run info: ;duration: 0.08913803100585938;num_run:00049 \n",
      "[INFO] [2016-08-16 07:52:46,675:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 50. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:46,677:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 0.00015904480464\n",
      "  classifier:sgd:average, Value: False\n",
      "  classifier:sgd:eta0, Value: 0.0296347437049\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:l1_ratio, Value: 3.76000156664e-05\n",
      "  classifier:sgd:learning_rate, Value: invscaling\n",
      "  classifier:sgd:loss, Value: hinge\n",
      "  classifier:sgd:n_iter, Value: 41\n",
      "  classifier:sgd:penalty, Value: elasticnet\n",
      "  classifier:sgd:power_t, Value: 0.794062565613\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0144083482858\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: nystroem_sampler\n",
      "  preprocessor:nystroem_sampler:kernel, Value: cosine\n",
      "  preprocessor:nystroem_sampler:n_components, Value: 1515\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/kernel_approximation.py:463: UserWarning: n_components > n_samples. This is not possible.\n",
      "n_components was set to n_samples, which results in inefficient evaluation of the full kernel.\n",
      "  warnings.warn(\"n_components > n_samples. This is not possible.\\n\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:47,742:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 50. configuration. Duration: 0.984060; loss: 0.860656; status 1; additional run info: ;duration: 0.9840602874755859;num_run:00050 \n",
      "[INFO] [2016-08-16 07:52:47,750:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 51. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:47,752:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 3\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 1\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 100\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:47,889:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 51. configuration. Duration: 0.097456; loss: 0.684426; status 1; additional run info: ;duration: 0.09745645523071289;num_run:00051 \n",
      "[INFO] [2016-08-16 07:52:47,897:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 52. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:47,899:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: k_nearest_neighbors\n",
      "  classifier:k_nearest_neighbors:n_neighbors, Value: 20\n",
      "  classifier:k_nearest_neighbors:p, Value: 1\n",
      "  classifier:k_nearest_neighbors:weights, Value: uniform\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:47,956:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 52. configuration. Duration: 0.024106; loss: 0.692623; status 1; additional run info: ;duration: 0.024105548858642578;num_run:00052 \n",
      "[INFO] [2016-08-16 07:52:47,962:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 53. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:47,963:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: True\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 1.67205021017\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 8\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 6\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "You are already timing task: index_run7\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:52:48,214:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:48,634:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 53. configuration. Duration: 0.610161; loss: 0.700820; status 1; additional run info: ;duration: 0.610161304473877;num_run:00053 \n",
      "[INFO] [2016-08-16 07:52:48,641:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 54. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:48,642:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.030551257175\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 9\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 20\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 467\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.563343199931\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: pca\n",
      "  preprocessor:pca:keep_variance, Value: 0.515451906206\n",
      "  preprocessor:pca:whiten, Value: True\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:49,113:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 54. configuration. Duration: 0.426763; loss: 0.782787; status 1; additional run info: ;duration: 0.42676329612731934;num_run:00054 \n",
      "[INFO] [2016-08-16 07:52:49,125:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 55. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:49,127:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 1.0\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 1\n",
      "  classifier:extra_trees:min_samples_split, Value: 2\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000719988233049\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: gini\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 3.79481172531\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 1\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 2\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:49,628:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 55. configuration. Duration: 0.426129; loss: 0.717213; status 1; additional run info: ;duration: 0.4261291027069092;num_run:00055 \n",
      "[INFO] [2016-08-16 07:52:49,635:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 56. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:49,636:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 4.53735847098\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 9\n",
      "  classifier:random_forest:min_samples_split, Value: 11\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00264323269243\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 11\n",
      "  preprocessor:gem:precond, Value: 0.441382077675\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:52:50,094:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.336066 1: 0.356557 2: 0.368852 3: 0.372951 4: 0.372951 5: 0.372951 6: 0.372951 7: 0.372951 8: 0.372951 9: 0.372951 10: 0.372951 11: 0.372951 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.372951 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [38, 12, 12, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.92  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 1) (1, 14) (1, 40)\n",
      "[INFO] [2016-08-16 07:52:50,100:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:52:50,102:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.891642 seconds\n",
      "[INFO] [2016-08-16 07:52:50,104:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:52:50,784:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 56. configuration. Duration: 1.112659; loss: 0.684426; status 1; additional run info: ;duration: 1.1126594543457031;num_run:00056 \n",
      "[INFO] [2016-08-16 07:52:50,790:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 57. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:50,791:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 3.77509988997\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 1\n",
      "  classifier:random_forest:min_samples_split, Value: 4\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:52:51,076:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 57. configuration. Duration: 0.248880; loss: 0.737705; status 1; additional run info: ;duration: 0.24887990951538086;num_run:00057 \n",
      "[INFO] [2016-08-16 07:52:51,082:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 58. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:51,083:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 0.0384013091944\n",
      "  classifier:libsvm_svc:gamma, Value: 0.543655430274\n",
      "  classifier:libsvm_svc:kernel, Value: rbf\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: True\n",
      "  classifier:libsvm_svc:tol, Value: 0.00478209894787\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000140331374358\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: pca\n",
      "  preprocessor:pca:keep_variance, Value: 0.95292659874\n",
      "  preprocessor:pca:whiten, Value: False\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:51,162:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 58. configuration. Duration: 0.050980; loss: 0.860656; status 1; additional run info: ;duration: 0.050980329513549805;num_run:00058 \n",
      "[INFO] [2016-08-16 07:52:51,168:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 59. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:51,169:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 0.680982525885\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 2\n",
      "  classifier:extra_trees:min_samples_split, Value: 16\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00335999889804\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: True\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 0.511421619119\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 20\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 11\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:51,515:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 59. configuration. Duration: 0.305785; loss: 0.811475; status 1; additional run info: ;duration: 0.3057849407196045;num_run:00059 \n",
      "[INFO] [2016-08-16 07:52:51,521:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 60. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:51,522:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: qda\n",
      "  classifier:qda:reg_param, Value: 4.37570629591\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00051743423577\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/discriminant_analysis.py:688: UserWarning: Variables are collinear\n",
      "  warnings.warn(\"Variables are collinear\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:51,623:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 60. configuration. Duration: 0.068121; loss: 0.905738; status 1; additional run info: ;duration: 0.06812095642089844;num_run:00060 \n",
      "[INFO] [2016-08-16 07:52:51,629:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 61. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:51,630:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: True\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 4.04339655244\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 12\n",
      "  classifier:extra_trees:min_samples_split, Value: 12\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 55.3443415821\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:51,814:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 61. configuration. Duration: 0.148920; loss: 0.700820; status 1; additional run info: ;duration: 0.14892029762268066;num_run:00061 \n",
      "[INFO] [2016-08-16 07:52:51,820:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 62. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:51,821:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: False\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 1.07294123924\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 12\n",
      "  classifier:random_forest:min_samples_split, Value: 18\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:gamma, Value: 6.69631373117e-05\n",
      "  preprocessor:kernel_pca:kernel, Value: rbf\n",
      "  preprocessor:kernel_pca:n_components, Value: 446\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run7\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:52:52,120:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:53,016:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 62. configuration. Duration: 1.086819; loss: 0.856557; status 1; additional run info: ;duration: 1.0868191719055176;num_run:00062 \n",
      "[INFO] [2016-08-16 07:52:53,024:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 63. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:53,026:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 1.51750461197\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 13\n",
      "  classifier:random_forest:min_samples_split, Value: 6\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.250169099735\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 88.0287717766\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:52:53,237:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 63. configuration. Duration: 0.174713; loss: 0.688525; status 1; additional run info: ;duration: 0.1747128963470459;num_run:00063 \n",
      "[INFO] [2016-08-16 07:52:53,243:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 64. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:53,244:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 0.0227063685249\n",
      "  classifier:bernoulli_nb:fit_prior, Value: True\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.294260475445\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: euclidean\n",
      "  preprocessor:feature_agglomeration:linkage, Value: average\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 200\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: max\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:52:53,289:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 64. configuration. Duration: 0.015303; loss: 0.811475; status 1; additional run info: ;duration: 0.01530313491821289;num_run:00064 \n",
      "[INFO] [2016-08-16 07:52:53,295:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 65. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:53,297:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 2.22043699158\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 4\n",
      "  classifier:random_forest:min_samples_split, Value: 15\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000557694994496\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:52:53,547:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 65. configuration. Duration: 0.212155; loss: 0.676230; status 1; additional run info: ;duration: 0.21215486526489258;num_run:00065 \n",
      "[INFO] [2016-08-16 07:52:53,554:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 66. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:52:53,556:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 39\n",
      "  classifier:lda:shrinkage, Value: None\n",
      "  classifier:lda:tol, Value: 4.21779542004e-05\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.132885184135\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 0.668836501037\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 1249\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/discriminant_analysis.py:387: UserWarning: Variables are collinear.\n",
      "  warnings.warn(\"Variables are collinear.\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:52:54,647:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 66. configuration. Duration: 1.029061; loss: 0.971311; status 1; additional run info: ;duration: 1.0290608406066895;num_run:00066 \n",
      "[INFO] [2016-08-16 07:52:54,768:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 55 training points for SMAC.\n",
      "[INFO] [2016-08-16 07:52:54,835:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.336066 1: 0.356557 2: 0.368852 3: 0.372951 4: 0.360656 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.372951 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.372951 39: 0.372951 40: 0.377049 41: 0.372951 42: 0.372951 43: 0.372951 44: 0.377049 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.372951\n",
      "\tMembers: [33, 8, 8, 8, 8, 33, 8, 8, 8, 33, 8, 8, 8, 8, 33, 8, 8, 8, 33, 8, 8, 8, 8, 33, 8, 8, 8, 8, 33, 8, 8, 8, 33, 8, 8, 8, 8, 33, 8, 8, 33, 8, 8, 8, 33, 8, 8, 8, 33, 8]\n",
      "\tWeights: [ 0.    0.    0.    0.    0.    0.    0.    0.    0.76  0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.24  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 14) (1, 40)\n",
      "[INFO] [2016-08-16 07:52:54,842:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:52:54,844:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.727591 seconds\n",
      "[INFO] [2016-08-16 07:52:54,847:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (59)!.\n",
      "[INFO] [2016-08-16 07:52:54,849:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (59)!\n",
      "[ERROR] [2016-08-16 07:52:54,860:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:52:56,899:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.336066 1: 0.356557 2: 0.368852 3: 0.372951 4: 0.360656 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.372951 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.372951 39: 0.372951 40: 0.377049 41: 0.372951 42: 0.372951 43: 0.372951 44: 0.377049 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.372951\n",
      "\tMembers: [30, 8, 8, 8, 8, 30, 8, 8, 8, 30, 8, 8, 8, 8, 30, 8, 8, 8, 30, 8, 8, 8, 8, 30, 8, 8, 8, 8, 30, 8, 8, 8, 30, 8, 8, 8, 8, 30, 8, 8, 30, 8, 8, 8, 30, 8, 8, 8, 30, 8]\n",
      "\tWeights: [ 0.    0.    0.    0.    0.    0.    0.    0.    0.76  0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.24  0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 14) (1, 40)\n",
      "[INFO] [2016-08-16 07:52:56,905:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:52:56,907:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.053093 seconds\n",
      "[INFO] [2016-08-16 07:52:56,909:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:53:05,719:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 10.95 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:53:05,725:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 67. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:05,726:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 9\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000235729688366\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:06,255:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 67. configuration. Duration: 0.484348; loss: 0.668033; status 1; additional run info: ;duration: 0.4843475818634033;num_run:00067 \n",
      "[INFO] [2016-08-16 07:53:06,262:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 68. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:06,263:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0264166532664\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 9\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 6\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 393\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.786710468821\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000488079067566\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: euclidean\n",
      "  preprocessor:feature_agglomeration:linkage, Value: average\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 123\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: median\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:53:06,944:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:53:07,183:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 68. configuration. Duration: 0.887842; loss: 0.672131; status 1; additional run info: ;duration: 0.8878421783447266;num_run:00068 \n",
      "[INFO] [2016-08-16 07:53:07,189:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 69. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:07,190:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 57.5873515211\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:07,719:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 69. configuration. Duration: 0.483470; loss: 0.663934; status 1; additional run info: ;duration: 0.48346996307373047;num_run:00069 \n",
      "[INFO] [2016-08-16 07:53:07,726:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 70. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:07,727:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0437093472947\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 7\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 4\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 149\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.693167152734\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00446346881981\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: cosine\n",
      "  preprocessor:feature_agglomeration:linkage, Value: average\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 281\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: mean\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:53:08,284:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 70. configuration. Duration: 0.520678; loss: 0.721311; status 1; additional run info: ;duration: 0.5206782817840576;num_run:00070 \n",
      "[INFO] [2016-08-16 07:53:08,291:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 71. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:08,292:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 3\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:08,841:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.336066 1: 0.356557 2: 0.368852 3: 0.372951 4: 0.360656 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.372951 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.372951 39: 0.372951 40: 0.377049 41: 0.372951 42: 0.372951 43: 0.372951 44: 0.377049 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.372951\n",
      "\tMembers: [30, 8, 8, 8, 8, 30, 8, 8, 8, 30, 8, 8, 8, 8, 30, 8, 8, 8, 30, 8, 8, 8, 8, 30, 8, 8, 8, 8, 30, 8, 8, 8, 30, 8, 8, 8, 8, 30, 8, 8, 30, 8, 8, 8, 30, 8, 8, 8, 30, 8]\n",
      "\tWeights: [ 0.    0.    0.    0.    0.    0.    0.    0.    0.76  0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.24  0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 14) (1, 40)\n",
      "[INFO] [2016-08-16 07:53:08,846:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:53:08,848:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.907761 seconds\n",
      "[INFO] [2016-08-16 07:53:08,849:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:53:08,883:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 71. configuration. Duration: 0.545248; loss: 0.659836; status 1; additional run info: ;duration: 0.5452477931976318;num_run:00071 \n",
      "[INFO] [2016-08-16 07:53:08,889:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 72. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:08,891:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 6.27815783649e-06\n",
      "  classifier:sgd:average, Value: False\n",
      "  classifier:sgd:eta0, Value: 0.0817613409425\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: invscaling\n",
      "  classifier:sgd:loss, Value: log\n",
      "  classifier:sgd:n_iter, Value: 21\n",
      "  classifier:sgd:penalty, Value: l2\n",
      "  classifier:sgd:power_t, Value: 0.180958599887\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.142269722722\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 0.908666044949\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 158\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:09,096:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 72. configuration. Duration: 0.132915; loss: 0.897541; status 1; additional run info: ;duration: 0.13291549682617188;num_run:00072 \n",
      "[INFO] [2016-08-16 07:53:09,102:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 73. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:09,104:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 3\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 50.0\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:09,600:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 73. configuration. Duration: 0.451949; loss: 0.668033; status 1; additional run info: ;duration: 0.451948881149292;num_run:00073 \n",
      "[INFO] [2016-08-16 07:53:09,606:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 74. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:09,607:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: qda\n",
      "  classifier:qda:reg_param, Value: 9.24649151176\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00110056298555\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:kernel, Value: cosine\n",
      "  preprocessor:kernel_pca:n_components, Value: 1243\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/discriminant_analysis.py:688: UserWarning: Variables are collinear\n",
      "  warnings.warn(\"Variables are collinear\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:53:10,148:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 74. configuration. Duration: 0.454872; loss: 1.073770; status 1; additional run info: ;duration: 0.45487165451049805;num_run:00074 \n",
      "[INFO] [2016-08-16 07:53:10,155:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 75. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:10,157:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 1.0\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 1\n",
      "  classifier:random_forest:min_samples_split, Value: 2\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 50.0\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:10,393:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 75. configuration. Duration: 0.196081; loss: 0.782787; status 1; additional run info: ;duration: 0.19608092308044434;num_run:00075 \n",
      "[INFO] [2016-08-16 07:53:10,400:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 76. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:10,401:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gaussian_nb\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00517965246807\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:53:10,444:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 76. configuration. Duration: 0.013873; loss: 0.823770; status 1; additional run info: ;duration: 0.013872861862182617;num_run:00076 \n",
      "[INFO] [2016-08-16 07:53:10,451:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 77. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:10,452:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 1.0\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 1\n",
      "  classifier:random_forest:min_samples_split, Value: 2\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0198498056687\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 50.0\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:10,686:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 77. configuration. Duration: 0.194153; loss: 0.782787; status 1; additional run info: ;duration: 0.1941533088684082;num_run:00077 \n",
      "[INFO] [2016-08-16 07:53:10,692:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 78. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:10,694:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 123\n",
      "  classifier:lda:shrinkage, Value: auto\n",
      "  classifier:lda:tol, Value: 0.000155721537166\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000178050638743\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 0.646134432482\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 3675\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:53:10,864:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:53:10,938:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:53:14,690:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.340164 1: 0.352459 2: 0.360656 3: 0.364754 4: 0.364754 5: 0.364754 6: 0.368852 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.368852 11: 0.368852 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.368852 16: 0.368852 17: 0.368852 18: 0.368852 19: 0.368852 20: 0.368852 21: 0.364754 22: 0.364754 23: 0.360656 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.377049 49: 0.377049\n",
      "\tMembers: [48, 42, 13, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 1, 49, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 27]\n",
      "\tWeights: [ 0.    0.02  0.    0.    0.    0.    0.    0.02  0.86  0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.02  0.    0.    0.    0.    0.    0.02  0.02]\n",
      "\tIdentifiers: (1, 6) (1, 13) (1, 14) (1, 21) (1, 40) (1, 63) (1, 71) (1, 73)\n",
      "[INFO] [2016-08-16 07:53:14,710:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.377049\n",
      "[INFO] [2016-08-16 07:53:14,716:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 3.856121 seconds\n",
      "[INFO] [2016-08-16 07:53:14,724:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (75)!.\n",
      "[INFO] [2016-08-16 07:53:14,732:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (75)!\n",
      "[INFO] [2016-08-16 07:53:39,741:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 78. configuration. Duration: 28.869441; loss: 0.860656; status 1; additional run info: ;duration: 28.86944079399109;num_run:00078 \n",
      "[INFO] [2016-08-16 07:53:39,905:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 67 training points for SMAC.\n",
      "[ERROR] [2016-08-16 07:53:40,863:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:53:40,925:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:53:42,810:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.340164 1: 0.352459 2: 0.360656 3: 0.364754 4: 0.364754 5: 0.364754 6: 0.368852 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.368852 11: 0.368852 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.368852 16: 0.368852 17: 0.368852 18: 0.368852 19: 0.368852 20: 0.368852 21: 0.364754 22: 0.364754 23: 0.360656 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.377049 49: 0.377049\n",
      "\tMembers: [48, 42, 13, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 1, 49, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 27]\n",
      "\tWeights: [ 0.    0.02  0.    0.    0.    0.    0.    0.02  0.86  0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.02  0.    0.    0.    0.    0.    0.02  0.02]\n",
      "\tIdentifiers: (1, 6) (1, 13) (1, 14) (1, 21) (1, 40) (1, 63) (1, 71) (1, 73)\n",
      "[INFO] [2016-08-16 07:53:42,816:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.377049\n",
      "[INFO] [2016-08-16 07:53:42,817:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.959399 seconds\n",
      "[INFO] [2016-08-16 07:53:42,819:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:53:52,008:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 12.1017 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:53:52,014:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 79. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:52,015:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:52,541:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 79. configuration. Duration: 0.482316; loss: 0.647541; status 1; additional run info: ;duration: 0.4823164939880371;num_run:00079 \n",
      "[INFO] [2016-08-16 07:53:52,546:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 80. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:52,547:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 468.293592608\n",
      "  classifier:libsvm_svc:gamma, Value: 0.959239406041\n",
      "  classifier:libsvm_svc:kernel, Value: rbf\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: False\n",
      "  classifier:libsvm_svc:tol, Value: 0.00731388567194\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: gini\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 3.11868949584\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 12\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 13\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:53:52,802:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 80. configuration. Duration: 0.216865; loss: 0.815574; status 1; additional run info: ;duration: 0.21686458587646484;num_run:00080 \n",
      "[INFO] [2016-08-16 07:53:52,808:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 81. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:52,810:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 3\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run9\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:53:52,866:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:53:52,915:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:53:53,408:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 81. configuration. Duration: 0.550602; loss: 0.659836; status 1; additional run info: ;duration: 0.5506021976470947;num_run:00081 \n",
      "[INFO] [2016-08-16 07:53:53,415:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 82. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:53,417:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0109297642034\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 1\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 20\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 284\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.739293931635\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00567671491912\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: pca\n",
      "  preprocessor:pca:keep_variance, Value: 0.955730415909\n",
      "  preprocessor:pca:whiten, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:53,623:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 82. configuration. Duration: 0.174173; loss: 0.704918; status 1; additional run info: ;duration: 0.17417311668395996;num_run:00082 \n",
      "[INFO] [2016-08-16 07:53:53,629:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 83. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:53,631:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:54,264:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 83. configuration. Duration: 0.586940; loss: 0.647541; status 1; additional run info: ;duration: 0.5869402885437012;num_run:00083 \n",
      "[INFO] [2016-08-16 07:53:54,270:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 84. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:54,272:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 89.7020369787\n",
      "  classifier:bernoulli_nb:fit_prior, Value: False\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000346762765191\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:53:54,346:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 84. configuration. Duration: 0.034073; loss: 0.897541; status 1; additional run info: ;duration: 0.0340728759765625;num_run:00084 \n",
      "[INFO] [2016-08-16 07:53:54,355:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 85. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:54,357:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:54,870:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.377049 14: 0.381148 15: 0.389344 16: 0.393443 17: 0.393443 18: 0.393443 19: 0.393443 20: 0.389344 21: 0.389344 22: 0.385246 23: 0.377049 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.381148 28: 0.381148 29: 0.377049 30: 0.377049 31: 0.377049 32: 0.377049 33: 0.377049 34: 0.377049 35: 0.377049 36: 0.377049 37: 0.377049 38: 0.385246 39: 0.389344 40: 0.389344 41: 0.389344 42: 0.389344 43: 0.389344 44: 0.389344 45: 0.389344 46: 0.389344 47: 0.389344 48: 0.389344 49: 0.389344\n",
      "\tMembers: [49, 26, 41, 12, 26, 26, 8, 8, 8, 8, 8, 8, 8, 16, 26, 26, 26, 8, 8, 26, 8, 8, 8, 26, 26, 26, 42, 1, 8, 26, 26, 25, 8, 8, 8, 3, 8, 18, 45, 48, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8]\n",
      "\tWeights: [ 0.    0.02  0.    0.02  0.    0.    0.    0.    0.54  0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.02  0.    0.02  0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.24  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.02  0.02  0.    0.    0.02  0.    0.    0.02  0.02]\n",
      "\tIdentifiers: (1, 6) (1, 8) (1, 14) (1, 21) (1, 27) (1, 30) (1, 39) (1, 40) (1, 63) (1, 65) (1, 69) (1, 73) (1, 79)\n",
      "[INFO] [2016-08-16 07:53:54,876:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.389344\n",
      "[INFO] [2016-08-16 07:53:54,878:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.016004 seconds\n",
      "[INFO] [2016-08-16 07:53:54,881:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (78)!.\n",
      "[INFO] [2016-08-16 07:53:54,884:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (78)!\n",
      "[ERROR] [2016-08-16 07:53:54,892:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:53:54,961:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:53:54,978:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 85. configuration. Duration: 0.567355; loss: 0.647541; status 1; additional run info: ;duration: 0.5673549175262451;num_run:00085 \n",
      "[INFO] [2016-08-16 07:53:54,985:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 86. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:54,986:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 1.16783380991\n",
      "  classifier:bernoulli_nb:fit_prior, Value: False\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: logcosh\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 116, in _ica_par\n",
      "    warnings.warn('FastICA did not converge. Consider increasing '\n",
      "UserWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:53:56,244:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 86. configuration. Duration: 1.252481; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:53:56,250:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 87. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:56,252:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.125602291896\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:53:56,796:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 87. configuration. Duration: 0.498615; loss: 0.647541; status 1; additional run info: ;duration: 0.4986145496368408;num_run:00087 \n",
      "[INFO] [2016-08-16 07:53:56,802:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 88. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:53:56,802:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.377049 22: 0.377049 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.368852 29: 0.368852 30: 0.364754 31: 0.377049 32: 0.385246 33: 0.389344 34: 0.389344 35: 0.389344 36: 0.389344 37: 0.389344 38: 0.389344 39: 0.385246 40: 0.385246 41: 0.385246 42: 0.385246 43: 0.385246 44: 0.385246 45: 0.385246 46: 0.385246 47: 0.385246 48: 0.385246 49: 0.385246\n",
      "\tMembers: [46, 24, 38, 11, 24, 24, 7, 7, 7, 7, 48, 7, 7, 7, 7, 24, 24, 24, 7, 7, 7, 13, 7, 7, 7, 7, 7, 7, 7, 24, 11, 38, 48, 18, 7, 7, 7, 7, 24, 7, 7, 7, 7, 7, 7, 7, 24, 48, 7, 7]\n",
      "\tWeights: [ 0.    0.    0.    0.    0.    0.    0.    0.62  0.    0.    0.    0.04\n",
      "  0.    0.02  0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.18  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.04  0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.06\n",
      "  0.  ]\n",
      "\tIdentifiers: (1, 14) (1, 21) (1, 25) (1, 31) (1, 40) (1, 63) (1, 79) (1, 82)[INFO] [2016-08-16 07:53:56,804:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.80143446159\n",
      "  classifier:adaboost:max_depth, Value: 5\n",
      "  classifier:adaboost:n_estimators, Value: 194\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:gamma, Value: 0.00790127386495\n",
      "  preprocessor:kernel_pca:kernel, Value: rbf\n",
      "  preprocessor:kernel_pca:n_components, Value: 152\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "\n",
      "[INFO] [2016-08-16 07:53:56,809:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.385246\n",
      "[INFO] [2016-08-16 07:53:56,810:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.922933 seconds\n",
      "[INFO] [2016-08-16 07:53:56,813:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (82)!.\n",
      "[INFO] [2016-08-16 07:53:56,816:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (82)!\n",
      "[ERROR] [2016-08-16 07:53:56,825:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:53:56,949:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:53:59,005:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.385246 26: 0.385246 27: 0.385246 28: 0.385246 29: 0.385246 30: 0.385246 31: 0.385246 32: 0.385246 33: 0.385246 34: 0.385246 35: 0.385246 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.377049 43: 0.377049 44: 0.377049 45: 0.377049 46: 0.377049 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [44, 22, 36, 10, 22, 22, 7, 7, 7, 7, 46, 7, 7, 7, 7, 22, 22, 22, 7, 7, 7, 7, 44, 2, 35, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 22, 7, 7, 22, 7, 7, 7, 7, 7, 7, 7, 21, 2, 7, 7]\n",
      "\tWeights: [ 0.    0.    0.04  0.    0.    0.    0.    0.64  0.    0.    0.02  0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.02  0.16  0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.02  0.    0.\n",
      "  0.    0.    0.    0.    0.    0.04  0.    0.02  0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 21) (1, 27) (1, 39) (1, 40) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:53:59,013:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:53:59,014:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.193091 seconds\n",
      "[INFO] [2016-08-16 07:53:59,017:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (84)!.\n",
      "[INFO] [2016-08-16 07:53:59,019:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (84)!\n",
      "[INFO] [2016-08-16 07:54:07,598:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 88. configuration. Duration: 10.672352; loss: 0.799180; status 1; additional run info: ;duration: 10.672351837158203;num_run:00088 \n",
      "[INFO] [2016-08-16 07:54:07,763:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 74 training points for SMAC.\n",
      "[ERROR] [2016-08-16 07:54:09,057:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:54:09,112:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:54:11,098:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.385246 26: 0.385246 27: 0.385246 28: 0.385246 29: 0.385246 30: 0.385246 31: 0.385246 32: 0.385246 33: 0.385246 34: 0.385246 35: 0.385246 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.377049 43: 0.377049 44: 0.377049 45: 0.377049 46: 0.377049 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [44, 22, 36, 10, 22, 22, 7, 7, 7, 7, 46, 7, 7, 7, 7, 22, 22, 22, 7, 7, 7, 7, 44, 2, 35, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 22, 7, 7, 22, 7, 7, 7, 7, 7, 7, 7, 21, 2, 7, 7]\n",
      "\tWeights: [ 0.    0.    0.04  0.    0.    0.    0.    0.64  0.    0.    0.02  0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.02  0.16  0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.02  0.    0.\n",
      "  0.    0.    0.    0.    0.    0.04  0.    0.02  0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 21) (1, 27) (1, 39) (1, 40) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:54:11,105:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:54:11,107:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.053967 seconds\n",
      "[INFO] [2016-08-16 07:54:11,109:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:54:20,040:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 12.2755 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:54:20,045:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 89. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:20,047:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:20,526:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 89. configuration. Duration: 0.436658; loss: 0.647541; status 1; additional run info: ;duration: 0.4366579055786133;num_run:00089 \n",
      "[INFO] [2016-08-16 07:54:20,531:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 90. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:20,533:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 207\n",
      "  classifier:lda:shrinkage, Value: manual\n",
      "  classifier:lda:shrinkage_factor, Value: 0.497327276651\n",
      "  classifier:lda:tol, Value: 1.02547648296e-05\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.270933580466\n",
      "  preprocessor:select_rates:mode, Value: fpr\n",
      "  preprocessor:select_rates:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:54:20,580:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 90. configuration. Duration: 0.020699; loss: 0.827869; status 1; additional run info: ;duration: 0.020699024200439453;num_run:00090 \n",
      "[INFO] [2016-08-16 07:54:20,586:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 91. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:20,587:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:21,090:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 91. configuration. Duration: 0.462179; loss: 0.647541; status 1; additional run info: ;duration: 0.46217918395996094;num_run:00091 \n",
      "[INFO] [2016-08-16 07:54:21,096:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 92. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:21,097:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 2245.7923256\n",
      "  classifier:libsvm_svc:gamma, Value: 0.000112257171296\n",
      "  classifier:libsvm_svc:kernel, Value: rbf\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: False\n",
      "  classifier:libsvm_svc:tol, Value: 5.99568531548e-05\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 2\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 13\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 14\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 65\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run12\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:54:21,147:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:54:21,205:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:54:21,591:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 92. configuration. Duration: 0.456091; loss: 0.713115; status 1; additional run info: ;duration: 0.45609068870544434;num_run:00092 \n",
      "[INFO] [2016-08-16 07:54:21,596:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 93. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:21,599:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:22,233:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 93. configuration. Duration: 0.586157; loss: 0.647541; status 1; additional run info: ;duration: 0.5861566066741943;num_run:00093 \n",
      "[INFO] [2016-08-16 07:54:22,241:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 94. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:22,242:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: True\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 2.13964151757\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 1\n",
      "  classifier:extra_trees:min_samples_split, Value: 15\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:coef0, Value: 0.696928506788\n",
      "  preprocessor:kernel_pca:kernel, Value: sigmoid\n",
      "  preprocessor:kernel_pca:n_components, Value: 1652\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:54:23,281:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 94. configuration. Duration: 0.953923; loss: 0.971311; status 1; additional run info: ;duration: 0.953923225402832;num_run:00094 \n",
      "[INFO] [2016-08-16 07:54:23,289:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 95. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:23,291:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:23,498:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.381148\n",
      "\tMembers: [42, 20, 34, 9, 20, 20, 6, 6, 6, 6, 44, 6, 6, 6, 6, 20, 20, 20, 6, 6, 6, 6, 42, 2, 33, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 42, 6, 6, 6, 6, 6, 44, 8, 28]\n",
      "\tWeights: [ 0.    0.    0.02  0.    0.    0.    0.66  0.    0.02  0.02  0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.12  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.02  0.    0.    0.    0.    0.02  0.02  0.    0.    0.    0.\n",
      "  0.    0.    0.    0.06  0.    0.04  0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 19) (1, 21) (1, 40) (1, 52) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:54:23,505:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:54:23,507:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.363186 seconds\n",
      "[INFO] [2016-08-16 07:54:23,509:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (88)!.\n",
      "[INFO] [2016-08-16 07:54:23,510:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (88)!\n",
      "[ERROR] [2016-08-16 07:54:23,518:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:54:23,577:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:54:23,874:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 95. configuration. Duration: 0.526535; loss: 0.647541; status 1; additional run info: ;duration: 0.5265350341796875;num_run:00095 \n",
      "[INFO] [2016-08-16 07:54:23,882:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 96. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:23,884:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.369195645178\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 3\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 4\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 383\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.474904422007\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000178367917347\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:54:24,457:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 96. configuration. Duration: 0.541717; loss: 0.790984; status 1; additional run info: ;duration: 0.5417165756225586;num_run:00096 \n",
      "[INFO] [2016-08-16 07:54:24,463:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 97. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:24,464:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:25,011:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 97. configuration. Duration: 0.502587; loss: 0.647541; status 1; additional run info: ;duration: 0.5025866031646729;num_run:00097 \n",
      "[INFO] [2016-08-16 07:54:25,017:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 98. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:25,019:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 165\n",
      "  classifier:lda:shrinkage, Value: None\n",
      "  classifier:lda:tol, Value: 0.00461882611568\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0033602023141\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.412584165757\n",
      "  preprocessor:select_rates:mode, Value: fwe\n",
      "  preprocessor:select_rates:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:54:25,070:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 98. configuration. Duration: 0.022011; loss: 0.844262; status 1; additional run info: ;duration: 0.02201080322265625;num_run:00098 \n",
      "[INFO] [2016-08-16 07:54:25,077:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 99. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:25,079:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:25,422:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.381148\n",
      "\tMembers: [40, 19, 32, 8, 19, 19, 5, 5, 5, 5, 42, 5, 5, 5, 5, 19, 19, 19, 5, 5, 5, 5, 40, 2, 31, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 40, 5, 5, 5, 5, 5, 42, 7, 26]\n",
      "\tWeights: [ 0.    0.    0.02  0.    0.    0.66  0.    0.02  0.02  0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.12  0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.02  0.02  0.    0.    0.    0.    0.    0.\n",
      "  0.    0.06  0.    0.04  0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 19) (1, 21) (1, 40) (1, 52) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:54:25,430:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:54:25,432:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.918160 seconds\n",
      "[INFO] [2016-08-16 07:54:25,434:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:54:25,689:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 99. configuration. Duration: 0.564104; loss: 0.647541; status 1; additional run info: ;duration: 0.5641043186187744;num_run:00099 \n",
      "[INFO] [2016-08-16 07:54:25,695:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 100. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:25,697:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 0.00295770524785\n",
      "  classifier:sgd:average, Value: True\n",
      "  classifier:sgd:eta0, Value: 0.0791358187109\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: optimal\n",
      "  classifier:sgd:loss, Value: squared_hinge\n",
      "  classifier:sgd:n_iter, Value: 253\n",
      "  classifier:sgd:penalty, Value: l2\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 15\n",
      "  preprocessor:gem:precond, Value: 0.0130724105216\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:54:26,132:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 100. configuration. Duration: 0.404355; loss: 0.758197; status 1; additional run info: ;duration: 0.4043548107147217;num_run:00100 \n",
      "[INFO] [2016-08-16 07:54:26,138:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 101. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:26,140:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:26,726:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 101. configuration. Duration: 0.539549; loss: 0.647541; status 1; additional run info: ;duration: 0.5395493507385254;num_run:00101 \n",
      "[INFO] [2016-08-16 07:54:26,733:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 102. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:26,734:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: multinomial_nb\n",
      "  classifier:multinomial_nb:alpha, Value: 1.57793623654\n",
      "  classifier:multinomial_nb:fit_prior, Value: False\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:54:26,781:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 102. configuration. Duration: 0.016250; loss: 0.844262; status 1; additional run info: ;duration: 0.0162503719329834;num_run:00102 \n",
      "[INFO] [2016-08-16 07:54:26,788:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 103. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:26,789:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:27,347:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 103. configuration. Duration: 0.512883; loss: 0.647541; status 1; additional run info: ;duration: 0.5128834247589111;num_run:00103 \n",
      "[INFO] [2016-08-16 07:54:27,354:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 104. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:27,356:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 0.000696549061563\n",
      "  classifier:sgd:average, Value: False\n",
      "  classifier:sgd:eta0, Value: 0.0359119060582\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: constant\n",
      "  classifier:sgd:loss, Value: log\n",
      "  classifier:sgd:n_iter, Value: 786\n",
      "  classifier:sgd:penalty, Value: l2\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run13\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:54:27,448:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:54:27,506:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:54:28,110:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 104. configuration. Duration: 0.723044; loss: 0.860656; status 1; additional run info: ;duration: 0.7230443954467773;num_run:00104 \n",
      "[INFO] [2016-08-16 07:54:28,117:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 105. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:28,120:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.754722385843\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 5\n",
      "  classifier:gradient_boosting:max_features, Value: 4.76296464731\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 3\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 7\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 241\n",
      "  classifier:gradient_boosting:subsample, Value: 0.485710310047\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.41950170311\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 77.8585470502\n",
      "  preprocessor:select_percentile_classification:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:29,323:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.381148\n",
      "\tMembers: [35, 17, 27, 7, 17, 17, 4, 4, 4, 4, 37, 4, 4, 4, 4, 17, 17, 17, 4, 4, 4, 4, 35, 1, 26, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 35, 4, 4, 4, 4, 4, 37, 6, 22]\n",
      "\tWeights: [ 0.    0.02  0.    0.    0.66  0.    0.02  0.02  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.12  0.    0.    0.    0.    0.02  0.    0.    0.\n",
      "  0.02  0.02  0.    0.    0.    0.    0.    0.    0.    0.06  0.    0.04\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 19) (1, 21) (1, 40) (1, 52) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:54:29,332:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:54:29,334:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.889778 seconds\n",
      "[INFO] [2016-08-16 07:54:29,336:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run13\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:54:31,350:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:54:31,409:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:54:31,452:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 105. configuration. Duration: 3.262542; loss: 0.950820; status 1; additional run info: ;duration: 3.2625417709350586;num_run:00105 \n",
      "[INFO] [2016-08-16 07:54:31,459:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 106. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:31,461:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 1.18850827931\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 3\n",
      "  classifier:random_forest:min_samples_split, Value: 17\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 16\n",
      "  preprocessor:gem:precond, Value: 0.0521570323336\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:54:32,014:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 106. configuration. Duration: 0.512922; loss: 0.704918; status 1; additional run info: ;duration: 0.5129220485687256;num_run:00106 \n",
      "[INFO] [2016-08-16 07:54:32,021:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 107. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:32,024:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.251753634483\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 8\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 17\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 349\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.892626970885\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 89.9904282829\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:54:32,583:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 107. configuration. Duration: 0.525461; loss: 0.795082; status 1; additional run info: ;duration: 0.525460958480835;num_run:00107 \n",
      "[INFO] [2016-08-16 07:54:32,763:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 85 training points for SMAC.\n",
      "[INFO] [2016-08-16 07:54:33,274:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.381148\n",
      "\tMembers: [35, 17, 27, 7, 17, 17, 4, 4, 4, 4, 37, 4, 4, 4, 4, 17, 17, 17, 4, 4, 4, 4, 35, 1, 26, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 35, 4, 4, 4, 4, 4, 37, 6, 22]\n",
      "\tWeights: [ 0.    0.02  0.    0.    0.66  0.    0.02  0.02  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.12  0.    0.    0.    0.    0.02  0.    0.    0.\n",
      "  0.02  0.02  0.    0.    0.    0.    0.    0.    0.    0.06  0.    0.04\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 19) (1, 21) (1, 40) (1, 52) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:54:33,280:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:54:33,281:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.935196 seconds\n",
      "[INFO] [2016-08-16 07:54:33,283:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run13\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:54:35,299:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:54:35,358:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:54:37,285:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.381148\n",
      "\tMembers: [34, 16, 26, 6, 16, 16, 3, 3, 3, 3, 36, 3, 3, 3, 3, 16, 16, 16, 3, 3, 3, 3, 34, 0, 25, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 34, 3, 3, 3, 3, 3, 36, 5, 21]\n",
      "\tWeights: [ 0.02  0.    0.    0.66  0.    0.02  0.02  0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.12  0.    0.    0.    0.    0.02  0.    0.    0.\n",
      "  0.02  0.02  0.    0.    0.    0.    0.    0.    0.    0.06  0.    0.04\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 19) (1, 21) (1, 40) (1, 52) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:54:37,293:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:54:37,295:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.000303 seconds\n",
      "[INFO] [2016-08-16 07:54:37,298:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:54:44,827:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 12.0615 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:54:44,833:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 108. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:44,834:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.0140929261221\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 5\n",
      "  classifier:gradient_boosting:max_features, Value: 1.98361471899\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 3\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 18\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 491\n",
      "  classifier:gradient_boosting:subsample, Value: 0.478262930842\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00174982231698\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 11.7187438086\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:55,449:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 108. configuration. Duration: 10.520200; loss: 0.946721; status 1; additional run info: ;duration: 10.5201997756958;num_run:00108 \n",
      "[INFO] [2016-08-16 07:54:55,455:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 109. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:55,456:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: True\n",
      "  classifier:extra_trees:criterion, Value: entropy\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 3.15808734576\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 13\n",
      "  classifier:extra_trees:min_samples_split, Value: 17\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00582881233453\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:coef0, Value: 0.707819425797\n",
      "  preprocessor:kernel_pca:degree, Value: 3\n",
      "  preprocessor:kernel_pca:gamma, Value: 0.471951347077\n",
      "  preprocessor:kernel_pca:kernel, Value: poly\n",
      "  preprocessor:kernel_pca:n_components, Value: 924\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:54:56,292:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 109. configuration. Duration: 0.755989; loss: 0.786885; status 1; additional run info: ;duration: 0.755988597869873;num_run:00109 \n",
      "[INFO] [2016-08-16 07:54:56,300:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 110. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:54:56,302:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00194838002235\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 13\n",
      "  preprocessor:gem:precond, Value: 0.467735915172\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:54:57,039:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 110. configuration. Duration: 0.687126; loss: 0.725410; status 1; additional run info: ;duration: 0.6871263980865479;num_run:00110 \n",
      "[INFO] [2016-08-16 07:54:57,218:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 88 training points for SMAC.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run13\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:54:57,371:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:54:57,431:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:54:59,300:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.381148\n",
      "\tMembers: [34, 16, 26, 6, 16, 16, 3, 3, 3, 3, 36, 3, 3, 3, 3, 16, 16, 16, 3, 3, 3, 3, 34, 0, 25, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 34, 3, 3, 3, 3, 3, 36, 5, 21]\n",
      "\tWeights: [ 0.02  0.    0.    0.66  0.    0.02  0.02  0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.12  0.    0.    0.    0.    0.02  0.    0.    0.\n",
      "  0.02  0.02  0.    0.    0.    0.    0.    0.    0.    0.06  0.    0.04\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 19) (1, 21) (1, 40) (1, 52) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:54:59,306:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:54:59,309:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.942131 seconds\n",
      "[INFO] [2016-08-16 07:54:59,310:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:55:12,969:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 15.7494 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:55:12,975:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 111. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:12,976:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 6\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:13,604:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 111. configuration. Duration: 0.574477; loss: 0.680328; status 1; additional run info: ;duration: 0.5744767189025879;num_run:00111 \n",
      "[INFO] [2016-08-16 07:55:13,611:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 112. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:13,613:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 0.00929438164542\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: squared_hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 99\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.120247338594\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 3.63940092656\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 1\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 15\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:55:13,981:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 112. configuration. Duration: 0.321251; loss: 0.754098; status 1; additional run info: ;duration: 0.32125091552734375;num_run:00112 \n",
      "[INFO] [2016-08-16 07:55:13,987:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 113. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:13,989:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:14,593:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 113. configuration. Duration: 0.549000; loss: 0.672131; status 1; additional run info: ;duration: 0.5490000247955322;num_run:00113 \n",
      "[INFO] [2016-08-16 07:55:14,600:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 114. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:14,602:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: k_nearest_neighbors\n",
      "  classifier:k_nearest_neighbors:n_neighbors, Value: 9\n",
      "  classifier:k_nearest_neighbors:p, Value: 1\n",
      "  classifier:k_nearest_neighbors:weights, Value: uniform\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000138480060248\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:kernel, Value: cosine\n",
      "  preprocessor:kernel_pca:n_components, Value: 1777\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:15,040:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 114. configuration. Duration: 0.401957; loss: 0.745902; status 1; additional run info: ;duration: 0.40195727348327637;num_run:00114 \n",
      "[INFO] [2016-08-16 07:55:15,047:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 115. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:15,049:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 8\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run13\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:55:15,374:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:55:15,440:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:55:15,678:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 115. configuration. Duration: 0.574211; loss: 0.676230; status 1; additional run info: ;duration: 0.5742108821868896;num_run:00115 \n",
      "[INFO] [2016-08-16 07:55:15,685:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 116. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:15,687:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.841568514067\n",
      "  classifier:adaboost:max_depth, Value: 2\n",
      "  classifier:adaboost:n_estimators, Value: 369\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: liblinear_svc_preprocessor\n",
      "  preprocessor:liblinear_svc_preprocessor:C, Value: 5.6949351956\n",
      "  preprocessor:liblinear_svc_preprocessor:dual, Constant: False\n",
      "  preprocessor:liblinear_svc_preprocessor:fit_intercept, Constant: True\n",
      "  preprocessor:liblinear_svc_preprocessor:intercept_scaling, Constant: 1\n",
      "  preprocessor:liblinear_svc_preprocessor:loss, Value: squared_hinge\n",
      "  preprocessor:liblinear_svc_preprocessor:multi_class, Constant: ovr\n",
      "  preprocessor:liblinear_svc_preprocessor:penalty, Constant: l1\n",
      "  preprocessor:liblinear_svc_preprocessor:tol, Value: 1.76018529899e-05\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:55:16,923:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 116. configuration. Duration: 1.177393; loss: 0.745902; status 1; additional run info: ;duration: 1.1773934364318848;num_run:00116 \n",
      "[INFO] [2016-08-16 07:55:16,930:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 117. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:16,932:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:17,489:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.381148\n",
      "\tMembers: [32, 14, 24, 5, 14, 14, 3, 3, 3, 3, 34, 3, 3, 3, 3, 14, 14, 14, 3, 3, 3, 3, 32, 0, 23, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 32, 3, 3, 3, 3, 3, 34, 4, 19]\n",
      "\tWeights: [ 0.02  0.    0.    0.66  0.02  0.02  0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.12  0.    0.    0.    0.    0.02  0.    0.    0.    0.02  0.02\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.06  0.    0.04  0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 19) (1, 21) (1, 40) (1, 52) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:55:17,497:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:55:17,499:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.130225 seconds\n",
      "[INFO] [2016-08-16 07:55:17,502:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:55:17,578:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 117. configuration. Duration: 0.591630; loss: 0.688525; status 1; additional run info: ;duration: 0.5916295051574707;num_run:00117 \n",
      "[INFO] [2016-08-16 07:55:17,586:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 118. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:17,588:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 49\n",
      "  classifier:lda:shrinkage, Value: auto\n",
      "  classifier:lda:tol, Value: 0.00431693849262\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 1.49959402131\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 106\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:17,716:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 118. configuration. Duration: 0.072633; loss: 0.860656; status 1; additional run info: ;duration: 0.07263302803039551;num_run:00118 \n",
      "[INFO] [2016-08-16 07:55:17,723:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 119. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:17,725:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:18,393:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 119. configuration. Duration: 0.613678; loss: 0.672131; status 1; additional run info: ;duration: 0.6136782169342041;num_run:00119 \n",
      "[INFO] [2016-08-16 07:55:18,402:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 120. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:18,404:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: proj_logit\n",
      "  classifier:proj_logit:max_epochs, Value: 16\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.0562833850085\n",
      "  preprocessor:select_rates:mode, Value: fwe\n",
      "  preprocessor:select_rates:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/feature_selection/base.py:80: UserWarning: No features were selected: either the data is too noisy or the selection test too strict.\n",
      "  UserWarning)\n",
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 148, in _pre_transform\n",
      "    .transform(Xt)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/select_rates.py\", line 72, in transform\n",
      "    \"%s removed all features.\" % self.__class__.__name__)\n",
      "ValueError: SelectRates removed all features.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:55:19,482:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 120. configuration. Duration: 1.071274; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:55:19,490:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 121. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:19,492:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 3\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run13\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:55:19,517:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:55:19,580:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:55:20,103:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 121. configuration. Duration: 0.556868; loss: 0.659836; status 1; additional run info: ;duration: 0.556868314743042;num_run:00121 \n",
      "[INFO] [2016-08-16 07:55:20,111:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 122. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:20,114:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.598744078036\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 7\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 12\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 187\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.332950950447\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0592577452007\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.345444684314\n",
      "  preprocessor:select_rates:mode, Value: fdr\n",
      "  preprocessor:select_rates:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:20,356:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 122. configuration. Duration: 0.205959; loss: 0.848361; status 1; additional run info: ;duration: 0.20595932006835938;num_run:00122 \n",
      "[INFO] [2016-08-16 07:55:20,363:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 123. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:20,366:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 9\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:20,959:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 123. configuration. Duration: 0.540544; loss: 0.684426; status 1; additional run info: ;duration: 0.5405442714691162;num_run:00123 \n",
      "[INFO] [2016-08-16 07:55:20,967:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 124. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:20,969:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: proj_logit\n",
      "  classifier:proj_logit:max_epochs, Value: 5\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: cosine\n",
      "  preprocessor:feature_agglomeration:linkage, Value: average\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 116\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: median\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:21,044:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 124. configuration. Duration: 0.032275; loss: 0.860656; status 1; additional run info: ;duration: 0.03227496147155762;num_run:00124 \n",
      "[INFO] [2016-08-16 07:55:21,052:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 125. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:21,055:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 5\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:21,541:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.381148 14: 0.381148 15: 0.381148 16: 0.381148 17: 0.381148 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.372951 22: 0.372951 23: 0.377049 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.381148 28: 0.381148 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.377049 41: 0.377049 42: 0.372951 43: 0.372951 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.377049 49: 0.381148\n",
      "\tMembers: [29, 12, 22, 5, 12, 12, 3, 3, 3, 3, 31, 3, 3, 3, 3, 12, 12, 12, 3, 3, 3, 3, 29, 0, 21, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 29, 3, 3, 3, 3, 3, 31, 4, 17]\n",
      "\tWeights: [ 0.02  0.    0.    0.66  0.02  0.02  0.    0.    0.    0.    0.    0.\n",
      "  0.12  0.    0.    0.    0.    0.02  0.    0.    0.    0.02  0.02  0.    0.\n",
      "  0.    0.    0.    0.    0.06  0.    0.04  0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 8) (1, 14) (1, 19) (1, 21) (1, 40) (1, 52) (1, 61) (1, 63) (1, 79) (1, 82)\n",
      "[INFO] [2016-08-16 07:55:21,548:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:55:21,551:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.038180 seconds\n",
      "[INFO] [2016-08-16 07:55:21,553:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:55:21,658:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 125. configuration. Duration: 0.550006; loss: 0.668033; status 1; additional run info: ;duration: 0.5500056743621826;num_run:00125 \n",
      "[INFO] [2016-08-16 07:55:21,667:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 126. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:21,669:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0102758029498\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 4\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 20\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 370\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.713879366557\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0811542628976\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: euclidean\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 250\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: median\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:22,244:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 126. configuration. Duration: 0.537631; loss: 0.684426; status 1; additional run info: ;duration: 0.5376310348510742;num_run:00126 \n",
      "[INFO] [2016-08-16 07:55:22,250:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 127. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:22,252:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00345710317446\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:22,862:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 127. configuration. Duration: 0.557615; loss: 0.688525; status 1; additional run info: ;duration: 0.557614803314209;num_run:00127 \n",
      "[INFO] [2016-08-16 07:55:22,869:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 128. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:22,871:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 49\n",
      "  classifier:lda:shrinkage, Value: auto\n",
      "  classifier:lda:tol, Value: 3.52865677017e-05\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0864867962725\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: euclidean\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 310\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: median\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:22,929:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 128. configuration. Duration: 0.025280; loss: 0.860656; status 1; additional run info: ;duration: 0.025279521942138672;num_run:00128 \n",
      "[INFO] [2016-08-16 07:55:22,936:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 129. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:22,938:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 2.91968662088\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 7\n",
      "  classifier:random_forest:min_samples_split, Value: 10\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0162769660733\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:23,190:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 129. configuration. Duration: 0.210661; loss: 0.696721; status 1; additional run info: ;duration: 0.21066069602966309;num_run:00129 \n",
      "[INFO] [2016-08-16 07:55:23,197:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 130. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:23,199:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 9\n",
      "  classifier:lda:shrinkage, Value: auto\n",
      "  classifier:lda:tol, Value: 2.99467158145e-05\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 6\n",
      "  preprocessor:gem:precond, Value: 0.377989414122\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:23,306:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 130. configuration. Duration: 0.062868; loss: 0.713115; status 1; additional run info: ;duration: 0.06286764144897461;num_run:00130 \n",
      "[INFO] [2016-08-16 07:55:23,313:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 131. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:23,315:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.0787897825807\n",
      "  classifier:adaboost:max_depth, Value: 4\n",
      "  classifier:adaboost:n_estimators, Value: 290\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run13\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:55:23,569:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:55:23,632:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:55:24,542:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 131. configuration. Duration: 1.172038; loss: 0.741803; status 1; additional run info: ;duration: 1.1720380783081055;num_run:00131 \n",
      "[INFO] [2016-08-16 07:55:24,550:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 132. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:24,551:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.284771318748\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 8\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 7\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 50\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.891702003902\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: True\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: gini\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 3.6809589602\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 16\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 6\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:55:24,863:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 132. configuration. Duration: 0.268478; loss: 0.729508; status 1; additional run info: ;duration: 0.2684783935546875;num_run:00132 \n",
      "[INFO] [2016-08-16 07:55:24,870:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 133. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:24,871:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: False\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 1.22532262467\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 12\n",
      "  classifier:random_forest:min_samples_split, Value: 15\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:25,216:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 133. configuration. Duration: 0.304640; loss: 0.696721; status 1; additional run info: ;duration: 0.3046400547027588;num_run:00133 \n",
      "[INFO] [2016-08-16 07:55:25,223:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 134. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:25,225:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 4.19487985279\n",
      "  classifier:libsvm_svc:gamma, Value: 0.53354242842\n",
      "  classifier:libsvm_svc:kernel, Value: rbf\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: False\n",
      "  classifier:libsvm_svc:tol, Value: 0.0960682255726\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00242775775823\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: pca\n",
      "  preprocessor:pca:keep_variance, Value: 0.927350573044\n",
      "  preprocessor:pca:whiten, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:55:25,317:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 134. configuration. Duration: 0.059646; loss: 0.782787; status 1; additional run info: ;duration: 0.0596463680267334;num_run:00134 \n",
      "[INFO] [2016-08-16 07:55:25,324:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 135. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:25,325:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 4.33232458859\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 14\n",
      "  classifier:random_forest:min_samples_split, Value: 18\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 18\n",
      "  preprocessor:gem:precond, Value: 0.256012088744\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:25,610:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.377049 14: 0.377049 15: 0.377049 16: 0.377049 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.377049 29: 0.377049 30: 0.377049 31: 0.377049 32: 0.377049 33: 0.377049 34: 0.377049 35: 0.377049 36: 0.377049 37: 0.377049 38: 0.377049 39: 0.377049 40: 0.377049 41: 0.377049 42: 0.377049 43: 0.377049 44: 0.377049 45: 0.377049 46: 0.377049 47: 0.377049 48: 0.377049 49: 0.377049\n",
      "\tMembers: [26, 11, 19, 4, 11, 11, 2, 2, 2, 2, 2, 2, 2, 11, 11, 2, 2, 2, 2, 2, 2, 2, 2, 2, 25, 2, 2, 2, 18, 2, 2, 23, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]\n",
      "\tWeights: [ 0.    0.    0.78  0.    0.02  0.    0.    0.    0.    0.    0.    0.1   0.\n",
      "  0.    0.    0.    0.    0.    0.02  0.02  0.    0.    0.    0.02  0.\n",
      "  0.02  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 14) (1, 21) (1, 40) (1, 61) (1, 63) (1, 69) (1, 73) (1, 79)\n",
      "[INFO] [2016-08-16 07:55:25,616:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.377049\n",
      "[INFO] [2016-08-16 07:55:25,618:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.052617 seconds\n",
      "[INFO] [2016-08-16 07:55:25,620:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (126)!.\n",
      "[INFO] [2016-08-16 07:55:25,623:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (126)!\n",
      "[ERROR] [2016-08-16 07:55:25,633:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:55:25,698:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:55:25,848:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 135. configuration. Duration: 0.479432; loss: 0.700820; status 1; additional run info: ;duration: 0.4794318675994873;num_run:00135 \n",
      "[INFO] [2016-08-16 07:55:25,855:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 136. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:25,857:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: True\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 0.588128709313\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 15\n",
      "  classifier:extra_trees:min_samples_split, Value: 15\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.124377321709\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 10\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 5\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 6\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 86\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:26,331:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 136. configuration. Duration: 0.425857; loss: 0.795082; status 1; additional run info: ;duration: 0.4258568286895752;num_run:00136 \n",
      "[INFO] [2016-08-16 07:55:26,338:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 137. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:26,340:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 0.802700607691\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 15\n",
      "  classifier:random_forest:min_samples_split, Value: 7\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00077613349477\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 10\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 10\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 3\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 95\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:26,826:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 137. configuration. Duration: 0.438260; loss: 0.750000; status 1; additional run info: ;duration: 0.4382603168487549;num_run:00137 \n",
      "[INFO] [2016-08-16 07:55:26,834:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 138. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:26,835:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 0.0157110782873\n",
      "  classifier:sgd:average, Value: False\n",
      "  classifier:sgd:eta0, Value: 0.0526962841652\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:l1_ratio, Value: 1.68232280645e-08\n",
      "  classifier:sgd:learning_rate, Value: constant\n",
      "  classifier:sgd:loss, Value: perceptron\n",
      "  classifier:sgd:n_iter, Value: 121\n",
      "  classifier:sgd:penalty, Value: elasticnet\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0114913918957\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:kernel, Value: cosine\n",
      "  preprocessor:kernel_pca:n_components, Value: 164\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:27,635:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 138. configuration. Duration: 0.723895; loss: 0.831967; status 1; additional run info: ;duration: 0.7238950729370117;num_run:00138 \n",
      "[INFO] [2016-08-16 07:55:27,643:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 139. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:27,645:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 3.06538605845\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 19\n",
      "  classifier:random_forest:min_samples_split, Value: 19\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0816291391888\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: manhattan\n",
      "  preprocessor:feature_agglomeration:linkage, Value: average\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 50\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: max\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:55:27,926:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.377049 14: 0.377049 15: 0.377049 16: 0.377049 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.381148 32: 0.385246 33: 0.385246 34: 0.385246 35: 0.385246 36: 0.389344 37: 0.389344 38: 0.389344 39: 0.389344 40: 0.385246 41: 0.385246 42: 0.385246 43: 0.385246 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [25, 11, 18, 4, 11, 11, 2, 2, 2, 2, 2, 2, 2, 11, 11, 2, 2, 2, 2, 2, 2, 2, 2, 2, 24, 2, 2, 2, 2, 2, 7, 7, 11, 2, 2, 2, 2, 2, 2, 2, 11, 2, 2, 2, 11, 2, 2, 2, 2, 2]\n",
      "\tWeights: [ 0.    0.    0.72  0.    0.02  0.    0.    0.04  0.    0.    0.    0.16\n",
      "  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.02  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 14) (1, 21) (1, 31) (1, 40) (1, 63) (1, 73) (1, 79)\n",
      "[INFO] [2016-08-16 07:55:27,933:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:55:27,935:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.307051 seconds\n",
      "[INFO] [2016-08-16 07:55:27,938:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (130)!.\n",
      "[INFO] [2016-08-16 07:55:27,940:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (130)!\n",
      "[ERROR] [2016-08-16 07:55:27,949:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:55:28,018:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:55:28,142:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 139. configuration. Duration: 0.454250; loss: 0.704918; status 1; additional run info: ;duration: 0.45424962043762207;num_run:00139 \n",
      "[INFO] [2016-08-16 07:55:28,150:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 140. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:28,152:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.596714345182\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 2\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 2\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 496\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.78319831193\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 7\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 2\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 10\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 68\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:30,304:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.377049 14: 0.377049 15: 0.377049 16: 0.377049 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.381148 32: 0.385246 33: 0.385246 34: 0.385246 35: 0.385246 36: 0.389344 37: 0.389344 38: 0.389344 39: 0.389344 40: 0.385246 41: 0.385246 42: 0.385246 43: 0.385246 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [25, 11, 18, 4, 11, 11, 2, 2, 2, 2, 2, 2, 2, 11, 11, 2, 2, 2, 2, 2, 2, 2, 2, 2, 24, 2, 2, 2, 2, 2, 7, 7, 11, 2, 2, 2, 2, 2, 2, 2, 11, 2, 2, 2, 11, 2, 2, 2, 2, 2]\n",
      "\tWeights: [ 0.    0.    0.72  0.    0.02  0.    0.    0.04  0.    0.    0.    0.16\n",
      "  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.02  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 14) (1, 21) (1, 31) (1, 40) (1, 63) (1, 73) (1, 79)\n",
      "[INFO] [2016-08-16 07:55:30,311:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:55:30,314:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.368931 seconds\n",
      "[INFO] [2016-08-16 07:55:30,316:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 60, in fit_predict_and_loss\n",
      "    return self.predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 115, in predict_and_loss\n",
      "    Y_optimization_pred, Y_valid_pred, Y_test_pred = self._predict()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 98, in _predict\n",
      "    self.Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/abstract_evaluator.py\", line 266, in _predict_proba\n",
      "    Y_pred = model.predict_proba(X, batch_size=1000)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 120, in predict_proba\n",
      "    target = self.predict_proba(X[0:2].copy())\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 112, in predict_proba\n",
      "    return self.pipeline_.steps[-1][-1].predict_proba(Xt)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/classification/xgradient_boosting.py\", line 141, in predict_proba\n",
      "    return self.estimator.predict_proba(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/xgboost/sklearn.py\", line 477, in predict_proba\n",
      "    ntree_limit=ntree_limit)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/xgboost/core.py\", line 939, in predict\n",
      "    self._validate_features(data)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/xgboost/core.py\", line 1179, in _validate_features\n",
      "    data.feature_names))\n",
      "ValueError: feature_names mismatch: ['f0', 'f1', 'f2', 'f3', 'f4', 'f5', 'f6', 'f7', 'f8', 'f9', 'f10', 'f11', 'f12', 'f13', 'f14', 'f15', 'f16', 'f17', 'f18', 'f19', 'f20', 'f21', 'f22', 'f23', 'f24', 'f25', 'f26', 'f27', 'f28', 'f29', 'f30', 'f31', 'f32', 'f33', 'f34', 'f35', 'f36', 'f37', 'f38', 'f39', 'f40', 'f41', 'f42', 'f43', 'f44', 'f45', 'f46', 'f47', 'f48', 'f49', 'f50', 'f51', 'f52', 'f53', 'f54', 'f55', 'f56', 'f57', 'f58', 'f59', 'f60', 'f61', 'f62', 'f63', 'f64', 'f65', 'f66', 'f67', 'f68', 'f69', 'f70', 'f71', 'f72', 'f73', 'f74', 'f75', 'f76', 'f77', 'f78', 'f79', 'f80', 'f81', 'f82', 'f83', 'f84', 'f85', 'f86', 'f87', 'f88', 'f89', 'f90', 'f91', 'f92', 'f93', 'f94', 'f95', 'f96', 'f97', 'f98', 'f99', 'f100', 'f101', 'f102', 'f103', 'f104', 'f105', 'f106', 'f107', 'f108', 'f109', 'f110', 'f111', 'f112', 'f113', 'f114', 'f115', 'f116', 'f117', 'f118', 'f119', 'f120', 'f121', 'f122', 'f123', 'f124', 'f125', 'f126', 'f127', 'f128', 'f129', 'f130', 'f131', 'f132', 'f133', 'f134', 'f135', 'f136', 'f137', 'f138', 'f139', 'f140', 'f141', 'f142', 'f143', 'f144', 'f145', 'f146', 'f147', 'f148', 'f149', 'f150', 'f151', 'f152', 'f153', 'f154', 'f155', 'f156', 'f157', 'f158', 'f159', 'f160', 'f161', 'f162', 'f163', 'f164', 'f165', 'f166', 'f167', 'f168', 'f169', 'f170', 'f171', 'f172', 'f173', 'f174', 'f175', 'f176', 'f177', 'f178', 'f179', 'f180', 'f181', 'f182', 'f183', 'f184', 'f185', 'f186', 'f187', 'f188', 'f189', 'f190', 'f191', 'f192', 'f193', 'f194', 'f195', 'f196', 'f197', 'f198', 'f199', 'f200', 'f201', 'f202', 'f203', 'f204', 'f205', 'f206', 'f207', 'f208', 'f209', 'f210', 'f211', 'f212', 'f213', 'f214', 'f215', 'f216', 'f217', 'f218', 'f219', 'f220', 'f221', 'f222', 'f223', 'f224', 'f225', 'f226', 'f227', 'f228', 'f229', 'f230', 'f231', 'f232', 'f233', 'f234', 'f235', 'f236', 'f237', 'f238', 'f239', 'f240', 'f241', 'f242', 'f243', 'f244', 'f245', 'f246', 'f247', 'f248', 'f249', 'f250', 'f251', 'f252', 'f253', 'f254', 'f255', 'f256', 'f257', 'f258', 'f259', 'f260', 'f261', 'f262', 'f263', 'f264', 'f265', 'f266', 'f267', 'f268', 'f269', 'f270', 'f271', 'f272', 'f273', 'f274', 'f275', 'f276', 'f277', 'f278', 'f279', 'f280', 'f281', 'f282', 'f283', 'f284', 'f285', 'f286', 'f287', 'f288', 'f289', 'f290', 'f291', 'f292', 'f293', 'f294', 'f295', 'f296', 'f297', 'f298', 'f299', 'f300', 'f301', 'f302', 'f303', 'f304', 'f305', 'f306', 'f307', 'f308', 'f309', 'f310', 'f311', 'f312', 'f313', 'f314', 'f315', 'f316', 'f317', 'f318', 'f319', 'f320', 'f321', 'f322', 'f323', 'f324', 'f325', 'f326', 'f327', 'f328', 'f329', 'f330', 'f331', 'f332', 'f333', 'f334', 'f335', 'f336', 'f337', 'f338', 'f339', 'f340', 'f341', 'f342', 'f343', 'f344', 'f345', 'f346', 'f347', 'f348', 'f349', 'f350', 'f351', 'f352', 'f353', 'f354', 'f355', 'f356', 'f357', 'f358', 'f359', 'f360', 'f361', 'f362', 'f363', 'f364', 'f365', 'f366', 'f367', 'f368', 'f369', 'f370', 'f371', 'f372', 'f373', 'f374', 'f375', 'f376', 'f377', 'f378', 'f379', 'f380', 'f381', 'f382', 'f383', 'f384', 'f385', 'f386', 'f387', 'f388', 'f389', 'f390', 'f391', 'f392', 'f393', 'f394', 'f395', 'f396', 'f397', 'f398', 'f399', 'f400', 'f401', 'f402', 'f403', 'f404', 'f405', 'f406', 'f407', 'f408', 'f409', 'f410', 'f411', 'f412', 'f413', 'f414', 'f415', 'f416', 'f417', 'f418', 'f419', 'f420', 'f421', 'f422', 'f423', 'f424', 'f425', 'f426', 'f427', 'f428', 'f429', 'f430', 'f431', 'f432', 'f433', 'f434', 'f435', 'f436', 'f437', 'f438', 'f439', 'f440', 'f441', 'f442', 'f443', 'f444', 'f445', 'f446', 'f447', 'f448', 'f449', 'f450', 'f451', 'f452', 'f453', 'f454', 'f455', 'f456', 'f457', 'f458', 'f459', 'f460', 'f461', 'f462', 'f463', 'f464', 'f465', 'f466', 'f467', 'f468', 'f469', 'f470', 'f471', 'f472', 'f473', 'f474', 'f475', 'f476', 'f477', 'f478', 'f479', 'f480', 'f481', 'f482', 'f483', 'f484', 'f485', 'f486', 'f487', 'f488', 'f489', 'f490', 'f491', 'f492', 'f493', 'f494', 'f495', 'f496', 'f497', 'f498', 'f499', 'f500', 'f501', 'f502', 'f503', 'f504', 'f505', 'f506', 'f507', 'f508', 'f509', 'f510', 'f511', 'f512', 'f513', 'f514', 'f515', 'f516', 'f517', 'f518', 'f519', 'f520', 'f521', 'f522', 'f523', 'f524', 'f525', 'f526', 'f527', 'f528', 'f529', 'f530', 'f531', 'f532', 'f533', 'f534', 'f535', 'f536', 'f537', 'f538', 'f539', 'f540', 'f541', 'f542', 'f543', 'f544', 'f545', 'f546', 'f547', 'f548', 'f549', 'f550', 'f551', 'f552', 'f553', 'f554', 'f555', 'f556', 'f557', 'f558', 'f559', 'f560', 'f561', 'f562', 'f563', 'f564', 'f565', 'f566', 'f567', 'f568', 'f569', 'f570', 'f571', 'f572', 'f573', 'f574', 'f575', 'f576', 'f577', 'f578', 'f579', 'f580', 'f581', 'f582', 'f583', 'f584', 'f585', 'f586', 'f587', 'f588', 'f589', 'f590', 'f591', 'f592', 'f593', 'f594', 'f595', 'f596', 'f597', 'f598', 'f599', 'f600', 'f601', 'f602', 'f603', 'f604', 'f605', 'f606', 'f607', 'f608', 'f609', 'f610', 'f611', 'f612', 'f613', 'f614', 'f615', 'f616', 'f617', 'f618', 'f619', 'f620', 'f621', 'f622', 'f623', 'f624', 'f625', 'f626', 'f627', 'f628', 'f629', 'f630', 'f631', 'f632', 'f633', 'f634', 'f635', 'f636', 'f637', 'f638', 'f639', 'f640', 'f641', 'f642', 'f643', 'f644', 'f645', 'f646', 'f647', 'f648', 'f649', 'f650', 'f651', 'f652', 'f653', 'f654', 'f655', 'f656', 'f657', 'f658', 'f659', 'f660', 'f661', 'f662', 'f663', 'f664', 'f665', 'f666', 'f667', 'f668', 'f669', 'f670', 'f671', 'f672', 'f673', 'f674', 'f675', 'f676', 'f677', 'f678', 'f679', 'f680', 'f681', 'f682', 'f683', 'f684', 'f685', 'f686', 'f687', 'f688', 'f689', 'f690', 'f691', 'f692', 'f693', 'f694', 'f695', 'f696', 'f697', 'f698', 'f699', 'f700', 'f701', 'f702', 'f703', 'f704', 'f705', 'f706', 'f707', 'f708', 'f709', 'f710', 'f711', 'f712', 'f713', 'f714', 'f715', 'f716', 'f717', 'f718', 'f719', 'f720', 'f721', 'f722', 'f723', 'f724', 'f725', 'f726', 'f727', 'f728', 'f729', 'f730', 'f731', 'f732', 'f733', 'f734', 'f735', 'f736', 'f737', 'f738', 'f739', 'f740', 'f741', 'f742', 'f743', 'f744', 'f745', 'f746', 'f747', 'f748', 'f749', 'f750', 'f751', 'f752', 'f753', 'f754', 'f755', 'f756', 'f757', 'f758', 'f759', 'f760', 'f761', 'f762', 'f763', 'f764', 'f765', 'f766', 'f767', 'f768', 'f769', 'f770', 'f771', 'f772', 'f773', 'f774', 'f775', 'f776', 'f777', 'f778', 'f779', 'f780', 'f781', 'f782', 'f783', 'f784', 'f785', 'f786', 'f787', 'f788', 'f789', 'f790', 'f791', 'f792', 'f793', 'f794', 'f795', 'f796', 'f797', 'f798', 'f799', 'f800', 'f801', 'f802', 'f803', 'f804', 'f805', 'f806', 'f807', 'f808', 'f809', 'f810', 'f811', 'f812', 'f813', 'f814', 'f815', 'f816', 'f817', 'f818', 'f819', 'f820', 'f821', 'f822', 'f823', 'f824', 'f825', 'f826', 'f827', 'f828', 'f829', 'f830', 'f831', 'f832', 'f833', 'f834', 'f835', 'f836', 'f837', 'f838', 'f839', 'f840', 'f841', 'f842', 'f843', 'f844', 'f845', 'f846', 'f847', 'f848', 'f849', 'f850', 'f851', 'f852', 'f853', 'f854', 'f855', 'f856', 'f857', 'f858', 'f859', 'f860', 'f861', 'f862', 'f863', 'f864', 'f865', 'f866', 'f867', 'f868', 'f869', 'f870', 'f871', 'f872', 'f873', 'f874', 'f875', 'f876', 'f877', 'f878', 'f879', 'f880', 'f881', 'f882', 'f883', 'f884', 'f885', 'f886', 'f887', 'f888', 'f889', 'f890', 'f891', 'f892', 'f893', 'f894', 'f895', 'f896', 'f897', 'f898', 'f899', 'f900', 'f901', 'f902', 'f903', 'f904', 'f905', 'f906', 'f907', 'f908', 'f909', 'f910', 'f911', 'f912', 'f913', 'f914', 'f915', 'f916', 'f917', 'f918', 'f919', 'f920', 'f921', 'f922', 'f923', 'f924', 'f925', 'f926', 'f927', 'f928', 'f929', 'f930', 'f931', 'f932', 'f933', 'f934', 'f935', 'f936', 'f937', 'f938', 'f939', 'f940', 'f941', 'f942', 'f943', 'f944', 'f945', 'f946', 'f947', 'f948', 'f949', 'f950', 'f951', 'f952', 'f953', 'f954', 'f955', 'f956', 'f957', 'f958', 'f959', 'f960', 'f961', 'f962', 'f963', 'f964', 'f965', 'f966', 'f967', 'f968', 'f969', 'f970', 'f971', 'f972', 'f973', 'f974', 'f975', 'f976', 'f977', 'f978', 'f979', 'f980', 'f981', 'f982', 'f983', 'f984', 'f985', 'f986', 'f987', 'f988', 'f989', 'f990', 'f991', 'f992', 'f993', 'f994', 'f995', 'f996', 'f997', 'f998', 'f999', 'f1000', 'f1001', 'f1002', 'f1003', 'f1004', 'f1005', 'f1006', 'f1007', 'f1008', 'f1009', 'f1010', 'f1011', 'f1012', 'f1013', 'f1014', 'f1015', 'f1016', 'f1017', 'f1018', 'f1019', 'f1020', 'f1021', 'f1022', 'f1023', 'f1024', 'f1025', 'f1026', 'f1027', 'f1028', 'f1029', 'f1030', 'f1031', 'f1032', 'f1033', 'f1034', 'f1035', 'f1036', 'f1037', 'f1038', 'f1039', 'f1040', 'f1041', 'f1042', 'f1043', 'f1044', 'f1045', 'f1046', 'f1047', 'f1048', 'f1049', 'f1050', 'f1051', 'f1052', 'f1053', 'f1054', 'f1055', 'f1056', 'f1057', 'f1058', 'f1059', 'f1060', 'f1061', 'f1062', 'f1063', 'f1064', 'f1065', 'f1066', 'f1067', 'f1068', 'f1069', 'f1070', 'f1071', 'f1072', 'f1073', 'f1074', 'f1075', 'f1076', 'f1077', 'f1078', 'f1079', 'f1080', 'f1081', 'f1082', 'f1083', 'f1084', 'f1085', 'f1086', 'f1087', 'f1088', 'f1089', 'f1090', 'f1091', 'f1092', 'f1093', 'f1094', 'f1095', 'f1096', 'f1097', 'f1098', 'f1099', 'f1100', 'f1101', 'f1102', 'f1103', 'f1104', 'f1105', 'f1106', 'f1107', 'f1108', 'f1109', 'f1110', 'f1111', 'f1112', 'f1113', 'f1114', 'f1115', 'f1116', 'f1117', 'f1118', 'f1119', 'f1120', 'f1121', 'f1122', 'f1123', 'f1124', 'f1125', 'f1126', 'f1127', 'f1128', 'f1129', 'f1130', 'f1131', 'f1132', 'f1133', 'f1134', 'f1135', 'f1136', 'f1137', 'f1138', 'f1139', 'f1140', 'f1141', 'f1142', 'f1143', 'f1144', 'f1145', 'f1146', 'f1147', 'f1148', 'f1149', 'f1150', 'f1151', 'f1152', 'f1153', 'f1154', 'f1155', 'f1156', 'f1157', 'f1158', 'f1159', 'f1160', 'f1161', 'f1162', 'f1163', 'f1164', 'f1165', 'f1166', 'f1167', 'f1168', 'f1169', 'f1170', 'f1171', 'f1172', 'f1173', 'f1174', 'f1175', 'f1176', 'f1177', 'f1178', 'f1179', 'f1180', 'f1181', 'f1182', 'f1183', 'f1184', 'f1185', 'f1186', 'f1187', 'f1188', 'f1189', 'f1190', 'f1191', 'f1192', 'f1193', 'f1194', 'f1195', 'f1196', 'f1197', 'f1198', 'f1199', 'f1200', 'f1201', 'f1202', 'f1203', 'f1204', 'f1205', 'f1206', 'f1207', 'f1208', 'f1209', 'f1210', 'f1211', 'f1212', 'f1213', 'f1214', 'f1215', 'f1216', 'f1217', 'f1218', 'f1219', 'f1220', 'f1221', 'f1222', 'f1223', 'f1224', 'f1225', 'f1226', 'f1227', 'f1228', 'f1229', 'f1230', 'f1231', 'f1232', 'f1233', 'f1234', 'f1235', 'f1236', 'f1237', 'f1238', 'f1239', 'f1240', 'f1241', 'f1242', 'f1243', 'f1244', 'f1245', 'f1246', 'f1247', 'f1248', 'f1249', 'f1250', 'f1251', 'f1252', 'f1253', 'f1254', 'f1255', 'f1256', 'f1257', 'f1258', 'f1259', 'f1260', 'f1261', 'f1262', 'f1263', 'f1264', 'f1265', 'f1266', 'f1267', 'f1268', 'f1269', 'f1270', 'f1271', 'f1272', 'f1273', 'f1274', 'f1275', 'f1276', 'f1277', 'f1278', 'f1279', 'f1280', 'f1281', 'f1282', 'f1283', 'f1284', 'f1285', 'f1286', 'f1287', 'f1288', 'f1289', 'f1290', 'f1291', 'f1292', 'f1293', 'f1294', 'f1295', 'f1296', 'f1297', 'f1298', 'f1299', 'f1300', 'f1301', 'f1302', 'f1303', 'f1304', 'f1305', 'f1306', 'f1307', 'f1308', 'f1309', 'f1310', 'f1311', 'f1312', 'f1313', 'f1314', 'f1315', 'f1316', 'f1317', 'f1318', 'f1319', 'f1320', 'f1321', 'f1322', 'f1323', 'f1324', 'f1325', 'f1326', 'f1327', 'f1328', 'f1329', 'f1330', 'f1331', 'f1332', 'f1333', 'f1334', 'f1335', 'f1336', 'f1337', 'f1338', 'f1339', 'f1340', 'f1341', 'f1342', 'f1343', 'f1344', 'f1345', 'f1346', 'f1347', 'f1348', 'f1349', 'f1350', 'f1351', 'f1352', 'f1353', 'f1354', 'f1355', 'f1356', 'f1357', 'f1358', 'f1359', 'f1360', 'f1361', 'f1362', 'f1363', 'f1364', 'f1365', 'f1366', 'f1367', 'f1368', 'f1369', 'f1370', 'f1371', 'f1372', 'f1373', 'f1374', 'f1375', 'f1376', 'f1377', 'f1378', 'f1379', 'f1380', 'f1381', 'f1382', 'f1383', 'f1384', 'f1385', 'f1386', 'f1387', 'f1388', 'f1389', 'f1390', 'f1391', 'f1392', 'f1393', 'f1394', 'f1395', 'f1396', 'f1397', 'f1398', 'f1399', 'f1400', 'f1401', 'f1402', 'f1403', 'f1404', 'f1405', 'f1406', 'f1407', 'f1408', 'f1409', 'f1410', 'f1411', 'f1412', 'f1413', 'f1414', 'f1415', 'f1416', 'f1417', 'f1418', 'f1419', 'f1420', 'f1421', 'f1422', 'f1423', 'f1424', 'f1425', 'f1426', 'f1427', 'f1428', 'f1429', 'f1430', 'f1431', 'f1432', 'f1433', 'f1434', 'f1435', 'f1436', 'f1437', 'f1438', 'f1439', 'f1440', 'f1441', 'f1442', 'f1443', 'f1444', 'f1445', 'f1446', 'f1447', 'f1448', 'f1449', 'f1450', 'f1451', 'f1452', 'f1453', 'f1454', 'f1455', 'f1456', 'f1457', 'f1458', 'f1459', 'f1460', 'f1461', 'f1462', 'f1463', 'f1464', 'f1465', 'f1466', 'f1467', 'f1468', 'f1469', 'f1470', 'f1471', 'f1472', 'f1473', 'f1474', 'f1475', 'f1476', 'f1477', 'f1478', 'f1479', 'f1480', 'f1481', 'f1482', 'f1483', 'f1484', 'f1485', 'f1486', 'f1487', 'f1488', 'f1489', 'f1490', 'f1491', 'f1492', 'f1493', 'f1494', 'f1495', 'f1496', 'f1497', 'f1498', 'f1499', 'f1500', 'f1501', 'f1502', 'f1503', 'f1504', 'f1505', 'f1506', 'f1507', 'f1508', 'f1509', 'f1510', 'f1511', 'f1512', 'f1513', 'f1514', 'f1515', 'f1516', 'f1517', 'f1518', 'f1519', 'f1520', 'f1521', 'f1522', 'f1523', 'f1524', 'f1525', 'f1526', 'f1527', 'f1528', 'f1529', 'f1530', 'f1531', 'f1532', 'f1533', 'f1534', 'f1535', 'f1536', 'f1537', 'f1538', 'f1539', 'f1540', 'f1541', 'f1542', 'f1543', 'f1544', 'f1545', 'f1546', 'f1547', 'f1548', 'f1549', 'f1550', 'f1551', 'f1552', 'f1553', 'f1554', 'f1555', 'f1556', 'f1557', 'f1558', 'f1559', 'f1560', 'f1561', 'f1562', 'f1563', 'f1564', 'f1565', 'f1566', 'f1567', 'f1568', 'f1569', 'f1570', 'f1571', 'f1572', 'f1573', 'f1574', 'f1575', 'f1576', 'f1577', 'f1578', 'f1579', 'f1580', 'f1581', 'f1582', 'f1583', 'f1584', 'f1585', 'f1586', 'f1587', 'f1588', 'f1589', 'f1590', 'f1591', 'f1592', 'f1593', 'f1594', 'f1595', 'f1596', 'f1597', 'f1598', 'f1599', 'f1600', 'f1601', 'f1602', 'f1603', 'f1604', 'f1605', 'f1606', 'f1607', 'f1608', 'f1609', 'f1610', 'f1611', 'f1612', 'f1613', 'f1614', 'f1615', 'f1616', 'f1617', 'f1618', 'f1619', 'f1620', 'f1621', 'f1622', 'f1623', 'f1624', 'f1625', 'f1626', 'f1627', 'f1628', 'f1629', 'f1630', 'f1631', 'f1632', 'f1633', 'f1634', 'f1635', 'f1636', 'f1637', 'f1638', 'f1639', 'f1640', 'f1641', 'f1642', 'f1643', 'f1644', 'f1645', 'f1646', 'f1647', 'f1648', 'f1649', 'f1650', 'f1651', 'f1652', 'f1653', 'f1654', 'f1655', 'f1656', 'f1657', 'f1658', 'f1659', 'f1660', 'f1661', 'f1662', 'f1663', 'f1664', 'f1665', 'f1666', 'f1667', 'f1668', 'f1669', 'f1670', 'f1671', 'f1672', 'f1673', 'f1674', 'f1675', 'f1676', 'f1677', 'f1678', 'f1679', 'f1680', 'f1681', 'f1682', 'f1683', 'f1684', 'f1685', 'f1686', 'f1687', 'f1688', 'f1689', 'f1690', 'f1691', 'f1692', 'f1693', 'f1694', 'f1695', 'f1696', 'f1697', 'f1698', 'f1699', 'f1700', 'f1701', 'f1702', 'f1703', 'f1704', 'f1705', 'f1706', 'f1707', 'f1708', 'f1709', 'f1710', 'f1711', 'f1712', 'f1713', 'f1714', 'f1715', 'f1716', 'f1717', 'f1718', 'f1719', 'f1720', 'f1721', 'f1722', 'f1723', 'f1724', 'f1725', 'f1726', 'f1727', 'f1728', 'f1729', 'f1730', 'f1731', 'f1732', 'f1733', 'f1734', 'f1735', 'f1736', 'f1737', 'f1738', 'f1739', 'f1740', 'f1741', 'f1742', 'f1743', 'f1744', 'f1745', 'f1746', 'f1747', 'f1748', 'f1749', 'f1750', 'f1751', 'f1752', 'f1753', 'f1754', 'f1755', 'f1756', 'f1757', 'f1758', 'f1759', 'f1760', 'f1761', 'f1762', 'f1763', 'f1764', 'f1765', 'f1766', 'f1767', 'f1768', 'f1769', 'f1770', 'f1771', 'f1772', 'f1773', 'f1774', 'f1775', 'f1776', 'f1777', 'f1778', 'f1779', 'f1780', 'f1781', 'f1782', 'f1783', 'f1784', 'f1785', 'f1786', 'f1787', 'f1788', 'f1789', 'f1790', 'f1791', 'f1792', 'f1793', 'f1794', 'f1795', 'f1796', 'f1797', 'f1798', 'f1799', 'f1800', 'f1801', 'f1802', 'f1803', 'f1804', 'f1805', 'f1806', 'f1807', 'f1808', 'f1809', 'f1810', 'f1811', 'f1812', 'f1813', 'f1814', 'f1815', 'f1816', 'f1817', 'f1818', 'f1819', 'f1820', 'f1821', 'f1822', 'f1823', 'f1824', 'f1825', 'f1826', 'f1827', 'f1828', 'f1829', 'f1830', 'f1831', 'f1832', 'f1833', 'f1834', 'f1835', 'f1836', 'f1837', 'f1838', 'f1839', 'f1840', 'f1841', 'f1842', 'f1843', 'f1844', 'f1845', 'f1846', 'f1847', 'f1848', 'f1849', 'f1850', 'f1851', 'f1852', 'f1853', 'f1854', 'f1855', 'f1856', 'f1857', 'f1858', 'f1859', 'f1860', 'f1861', 'f1862', 'f1863', 'f1864', 'f1865', 'f1866', 'f1867', 'f1868', 'f1869', 'f1870', 'f1871', 'f1872', 'f1873', 'f1874', 'f1875', 'f1876', 'f1877', 'f1878', 'f1879', 'f1880', 'f1881', 'f1882', 'f1883', 'f1884', 'f1885', 'f1886', 'f1887', 'f1888', 'f1889', 'f1890', 'f1891', 'f1892', 'f1893', 'f1894', 'f1895', 'f1896', 'f1897', 'f1898', 'f1899', 'f1900', 'f1901', 'f1902', 'f1903', 'f1904', 'f1905', 'f1906', 'f1907', 'f1908', 'f1909', 'f1910', 'f1911', 'f1912', 'f1913', 'f1914', 'f1915', 'f1916', 'f1917', 'f1918', 'f1919', 'f1920', 'f1921', 'f1922', 'f1923', 'f1924', 'f1925', 'f1926', 'f1927', 'f1928', 'f1929', 'f1930', 'f1931', 'f1932', 'f1933', 'f1934', 'f1935', 'f1936', 'f1937', 'f1938', 'f1939', 'f1940', 'f1941', 'f1942', 'f1943', 'f1944', 'f1945', 'f1946', 'f1947', 'f1948', 'f1949', 'f1950', 'f1951', 'f1952', 'f1953', 'f1954', 'f1955', 'f1956', 'f1957', 'f1958', 'f1959', 'f1960', 'f1961', 'f1962', 'f1963', 'f1964', 'f1965', 'f1966', 'f1967', 'f1968', 'f1969', 'f1970', 'f1971', 'f1972', 'f1973', 'f1974', 'f1975', 'f1976', 'f1977', 'f1978', 'f1979', 'f1980', 'f1981', 'f1982', 'f1983', 'f1984', 'f1985', 'f1986', 'f1987', 'f1988', 'f1989', 'f1990', 'f1991', 'f1992', 'f1993', 'f1994', 'f1995', 'f1996', 'f1997', 'f1998', 'f1999', 'f2000', 'f2001', 'f2002', 'f2003', 'f2004', 'f2005', 'f2006', 'f2007', 'f2008', 'f2009', 'f2010', 'f2011', 'f2012', 'f2013', 'f2014', 'f2015', 'f2016', 'f2017', 'f2018', 'f2019', 'f2020', 'f2021', 'f2022', 'f2023', 'f2024', 'f2025', 'f2026', 'f2027', 'f2028', 'f2029', 'f2030', 'f2031', 'f2032', 'f2033', 'f2034', 'f2035', 'f2036', 'f2037', 'f2038', 'f2039', 'f2040', 'f2041', 'f2042', 'f2043', 'f2044', 'f2045', 'f2046', 'f2047', 'f2048', 'f2049', 'f2050', 'f2051', 'f2052', 'f2053', 'f2054', 'f2055', 'f2056', 'f2057', 'f2058', 'f2059', 'f2060', 'f2061', 'f2062', 'f2063', 'f2064', 'f2065', 'f2066', 'f2067', 'f2068', 'f2069', 'f2070', 'f2071', 'f2072', 'f2073', 'f2074', 'f2075', 'f2076', 'f2077', 'f2078', 'f2079', 'f2080', 'f2081', 'f2082', 'f2083', 'f2084', 'f2085', 'f2086', 'f2087', 'f2088', 'f2089', 'f2090', 'f2091', 'f2092', 'f2093', 'f2094', 'f2095', 'f2096', 'f2097', 'f2098', 'f2099', 'f2100', 'f2101', 'f2102', 'f2103', 'f2104', 'f2105', 'f2106', 'f2107', 'f2108', 'f2109', 'f2110', 'f2111', 'f2112', 'f2113', 'f2114', 'f2115', 'f2116', 'f2117', 'f2118', 'f2119', 'f2120', 'f2121', 'f2122', 'f2123', 'f2124', 'f2125', 'f2126', 'f2127', 'f2128', 'f2129', 'f2130', 'f2131', 'f2132', 'f2133', 'f2134', 'f2135', 'f2136', 'f2137', 'f2138', 'f2139', 'f2140', 'f2141', 'f2142', 'f2143', 'f2144', 'f2145', 'f2146', 'f2147', 'f2148', 'f2149', 'f2150', 'f2151', 'f2152', 'f2153', 'f2154', 'f2155', 'f2156', 'f2157', 'f2158', 'f2159', 'f2160', 'f2161', 'f2162', 'f2163', 'f2164', 'f2165', 'f2166', 'f2167', 'f2168', 'f2169', 'f2170', 'f2171', 'f2172', 'f2173', 'f2174', 'f2175', 'f2176', 'f2177', 'f2178', 'f2179', 'f2180', 'f2181', 'f2182', 'f2183', 'f2184', 'f2185', 'f2186', 'f2187', 'f2188', 'f2189', 'f2190', 'f2191', 'f2192', 'f2193', 'f2194', 'f2195', 'f2196', 'f2197', 'f2198', 'f2199', 'f2200', 'f2201', 'f2202', 'f2203', 'f2204', 'f2205', 'f2206', 'f2207', 'f2208', 'f2209', 'f2210', 'f2211', 'f2212', 'f2213', 'f2214', 'f2215', 'f2216', 'f2217', 'f2218', 'f2219', 'f2220', 'f2221', 'f2222', 'f2223', 'f2224', 'f2225', 'f2226', 'f2227', 'f2228', 'f2229', 'f2230', 'f2231', 'f2232', 'f2233', 'f2234', 'f2235', 'f2236', 'f2237', 'f2238', 'f2239', 'f2240', 'f2241', 'f2242', 'f2243', 'f2244', 'f2245', 'f2246', 'f2247', 'f2248', 'f2249', 'f2250', 'f2251', 'f2252', 'f2253', 'f2254', 'f2255', 'f2256', 'f2257', 'f2258', 'f2259', 'f2260', 'f2261', 'f2262', 'f2263', 'f2264', 'f2265', 'f2266', 'f2267', 'f2268', 'f2269', 'f2270', 'f2271', 'f2272', 'f2273', 'f2274', 'f2275', 'f2276', 'f2277', 'f2278', 'f2279', 'f2280', 'f2281', 'f2282', 'f2283', 'f2284', 'f2285', 'f2286', 'f2287', 'f2288', 'f2289', 'f2290', 'f2291', 'f2292', 'f2293', 'f2294', 'f2295', 'f2296', 'f2297', 'f2298', 'f2299', 'f2300', 'f2301', 'f2302', 'f2303', 'f2304', 'f2305', 'f2306', 'f2307', 'f2308', 'f2309', 'f2310', 'f2311', 'f2312', 'f2313', 'f2314', 'f2315', 'f2316', 'f2317', 'f2318', 'f2319', 'f2320', 'f2321', 'f2322', 'f2323', 'f2324', 'f2325', 'f2326', 'f2327', 'f2328', 'f2329', 'f2330', 'f2331', 'f2332', 'f2333', 'f2334', 'f2335', 'f2336', 'f2337', 'f2338', 'f2339', 'f2340', 'f2341', 'f2342', 'f2343', 'f2344', 'f2345', 'f2346', 'f2347', 'f2348', 'f2349', 'f2350', 'f2351', 'f2352', 'f2353', 'f2354', 'f2355', 'f2356', 'f2357', 'f2358', 'f2359', 'f2360', 'f2361', 'f2362', 'f2363', 'f2364', 'f2365', 'f2366', 'f2367', 'f2368', 'f2369', 'f2370', 'f2371', 'f2372', 'f2373', 'f2374', 'f2375', 'f2376', 'f2377', 'f2378', 'f2379', 'f2380', 'f2381', 'f2382', 'f2383', 'f2384', 'f2385', 'f2386', 'f2387', 'f2388', 'f2389', 'f2390', 'f2391', 'f2392', 'f2393', 'f2394', 'f2395', 'f2396', 'f2397'] ['f0', 'f1', 'f2', 'f3', 'f4', 'f5', 'f6', 'f7', 'f8', 'f9', 'f10', 'f11', 'f12', 'f13', 'f14', 'f15', 'f16', 'f17', 'f18', 'f19', 'f20', 'f21', 'f22', 'f23', 'f24', 'f25', 'f26', 'f27', 'f28', 'f29', 'f30', 'f31', 'f32', 'f33', 'f34', 'f35', 'f36', 'f37', 'f38', 'f39', 'f40', 'f41', 'f42', 'f43', 'f44', 'f45', 'f46', 'f47', 'f48', 'f49', 'f50', 'f51', 'f52', 'f53', 'f54', 'f55', 'f56', 'f57', 'f58', 'f59', 'f60', 'f61', 'f62', 'f63', 'f64', 'f65', 'f66', 'f67', 'f68', 'f69', 'f70', 'f71', 'f72', 'f73', 'f74', 'f75', 'f76', 'f77', 'f78', 'f79', 'f80', 'f81', 'f82', 'f83', 'f84', 'f85', 'f86', 'f87', 'f88', 'f89', 'f90', 'f91', 'f92', 'f93', 'f94', 'f95', 'f96', 'f97', 'f98', 'f99', 'f100', 'f101', 'f102', 'f103', 'f104', 'f105', 'f106', 'f107', 'f108', 'f109', 'f110', 'f111', 'f112', 'f113', 'f114', 'f115', 'f116', 'f117', 'f118', 'f119', 'f120', 'f121', 'f122', 'f123', 'f124', 'f125', 'f126', 'f127', 'f128', 'f129', 'f130', 'f131', 'f132', 'f133', 'f134', 'f135', 'f136', 'f137', 'f138', 'f139', 'f140', 'f141', 'f142', 'f143', 'f144', 'f145', 'f146', 'f147', 'f148', 'f149', 'f150', 'f151', 'f152', 'f153', 'f154', 'f155', 'f156', 'f157', 'f158', 'f159', 'f160', 'f161', 'f162', 'f163', 'f164', 'f165', 'f166', 'f167', 'f168', 'f169', 'f170', 'f171', 'f172', 'f173', 'f174', 'f175', 'f176', 'f177', 'f178', 'f179', 'f180', 'f181', 'f182', 'f183', 'f184', 'f185', 'f186', 'f187', 'f188', 'f189', 'f190', 'f191', 'f192', 'f193', 'f194', 'f195', 'f196', 'f197', 'f198', 'f199', 'f200', 'f201', 'f202', 'f203', 'f204', 'f205', 'f206', 'f207', 'f208', 'f209', 'f210', 'f211', 'f212', 'f213', 'f214', 'f215', 'f216', 'f217', 'f218', 'f219', 'f220', 'f221', 'f222', 'f223', 'f224', 'f225', 'f226', 'f227', 'f228', 'f229', 'f230', 'f231', 'f232', 'f233', 'f234', 'f235', 'f236', 'f237', 'f238', 'f239', 'f240', 'f241', 'f242', 'f243', 'f244', 'f245', 'f246', 'f247', 'f248', 'f249', 'f250', 'f251', 'f252', 'f253', 'f254', 'f255', 'f256', 'f257', 'f258', 'f259', 'f260', 'f261', 'f262', 'f263', 'f264', 'f265', 'f266', 'f267', 'f268', 'f269', 'f270', 'f271', 'f272', 'f273', 'f274', 'f275', 'f276', 'f277', 'f278', 'f279', 'f280', 'f281', 'f282', 'f283', 'f284', 'f285', 'f286', 'f287', 'f288', 'f289', 'f290', 'f291', 'f292', 'f293', 'f294', 'f295', 'f296', 'f297', 'f298', 'f299', 'f300', 'f301', 'f302', 'f303', 'f304', 'f305', 'f306', 'f307', 'f308', 'f309', 'f310', 'f311', 'f312', 'f313', 'f314', 'f315', 'f316', 'f317', 'f318', 'f319', 'f320', 'f321', 'f322', 'f323', 'f324', 'f325', 'f326', 'f327', 'f328', 'f329', 'f330', 'f331', 'f332', 'f333', 'f334', 'f335', 'f336', 'f337', 'f338', 'f339', 'f340', 'f341', 'f342', 'f343', 'f344', 'f345', 'f346', 'f347', 'f348', 'f349', 'f350', 'f351', 'f352', 'f353', 'f354', 'f355', 'f356', 'f357', 'f358', 'f359', 'f360', 'f361', 'f362', 'f363', 'f364', 'f365', 'f366', 'f367', 'f368', 'f369', 'f370', 'f371', 'f372', 'f373', 'f374', 'f375', 'f376', 'f377', 'f378', 'f379', 'f380', 'f381', 'f382', 'f383', 'f384', 'f385', 'f386', 'f387', 'f388', 'f389', 'f390', 'f391', 'f392', 'f393', 'f394', 'f395', 'f396', 'f397', 'f398', 'f399', 'f400', 'f401', 'f402', 'f403', 'f404', 'f405', 'f406', 'f407', 'f408', 'f409', 'f410', 'f411', 'f412', 'f413', 'f414', 'f415', 'f416', 'f417', 'f418', 'f419', 'f420', 'f421', 'f422', 'f423', 'f424', 'f425', 'f426', 'f427', 'f428', 'f429', 'f430', 'f431', 'f432', 'f433', 'f434', 'f435', 'f436', 'f437', 'f438', 'f439', 'f440', 'f441', 'f442', 'f443', 'f444', 'f445', 'f446', 'f447', 'f448', 'f449', 'f450', 'f451', 'f452', 'f453', 'f454', 'f455', 'f456', 'f457', 'f458', 'f459', 'f460', 'f461', 'f462', 'f463', 'f464', 'f465', 'f466', 'f467', 'f468', 'f469', 'f470', 'f471', 'f472', 'f473', 'f474', 'f475', 'f476', 'f477', 'f478', 'f479', 'f480', 'f481', 'f482', 'f483', 'f484', 'f485', 'f486', 'f487', 'f488', 'f489', 'f490', 'f491', 'f492', 'f493', 'f494', 'f495', 'f496', 'f497', 'f498', 'f499', 'f500', 'f501', 'f502', 'f503', 'f504', 'f505', 'f506', 'f507', 'f508', 'f509', 'f510', 'f511', 'f512', 'f513', 'f514', 'f515', 'f516', 'f517', 'f518', 'f519', 'f520', 'f521', 'f522', 'f523', 'f524', 'f525', 'f526', 'f527', 'f528', 'f529', 'f530', 'f531', 'f532', 'f533', 'f534', 'f535', 'f536', 'f537', 'f538', 'f539', 'f540', 'f541', 'f542', 'f543', 'f544', 'f545', 'f546', 'f547', 'f548', 'f549', 'f550', 'f551', 'f552', 'f553', 'f554', 'f555', 'f556', 'f557', 'f558', 'f559', 'f560', 'f561', 'f562', 'f563', 'f564', 'f565', 'f566', 'f567', 'f568', 'f569', 'f570', 'f571', 'f572', 'f573', 'f574', 'f575', 'f576', 'f577', 'f578', 'f579', 'f580', 'f581', 'f582', 'f583', 'f584', 'f585', 'f586', 'f587', 'f588', 'f589', 'f590', 'f591', 'f592', 'f593', 'f594', 'f595', 'f596', 'f597', 'f598', 'f599', 'f600', 'f601', 'f602', 'f603', 'f604', 'f605', 'f606', 'f607', 'f608', 'f609', 'f610', 'f611', 'f612', 'f613', 'f614', 'f615', 'f616', 'f617', 'f618', 'f619', 'f620', 'f621', 'f622', 'f623', 'f624', 'f625', 'f626', 'f627', 'f628', 'f629', 'f630', 'f631', 'f632', 'f633', 'f634', 'f635', 'f636', 'f637', 'f638', 'f639', 'f640', 'f641', 'f642', 'f643', 'f644', 'f645', 'f646', 'f647', 'f648', 'f649', 'f650', 'f651', 'f652', 'f653', 'f654', 'f655', 'f656', 'f657', 'f658', 'f659', 'f660', 'f661', 'f662', 'f663', 'f664', 'f665', 'f666', 'f667', 'f668', 'f669', 'f670', 'f671', 'f672', 'f673', 'f674', 'f675', 'f676', 'f677', 'f678', 'f679', 'f680', 'f681', 'f682', 'f683', 'f684', 'f685', 'f686', 'f687', 'f688', 'f689', 'f690', 'f691', 'f692', 'f693', 'f694', 'f695', 'f696', 'f697', 'f698', 'f699', 'f700', 'f701', 'f702', 'f703', 'f704', 'f705', 'f706', 'f707', 'f708', 'f709', 'f710', 'f711', 'f712', 'f713', 'f714', 'f715', 'f716', 'f717', 'f718', 'f719', 'f720', 'f721', 'f722', 'f723', 'f724', 'f725', 'f726', 'f727', 'f728', 'f729', 'f730', 'f731', 'f732', 'f733', 'f734', 'f735', 'f736', 'f737', 'f738', 'f739', 'f740', 'f741', 'f742', 'f743', 'f744', 'f745', 'f746', 'f747', 'f748', 'f749', 'f750', 'f751', 'f752', 'f753', 'f754', 'f755', 'f756', 'f757', 'f758', 'f759', 'f760', 'f761', 'f762', 'f763', 'f764', 'f765', 'f766', 'f767', 'f768', 'f769', 'f770', 'f771', 'f772', 'f773', 'f774', 'f775', 'f776', 'f777', 'f778', 'f779', 'f780', 'f781', 'f782', 'f783', 'f784', 'f785', 'f786', 'f787', 'f788', 'f789', 'f790', 'f791', 'f792', 'f793', 'f794', 'f795', 'f796', 'f797', 'f798', 'f799', 'f800', 'f801', 'f802', 'f803', 'f804', 'f805', 'f806', 'f807', 'f808', 'f809', 'f810', 'f811', 'f812', 'f813', 'f814', 'f815', 'f816', 'f817', 'f818', 'f819', 'f820', 'f821', 'f822', 'f823', 'f824', 'f825', 'f826', 'f827', 'f828', 'f829', 'f830', 'f831', 'f832', 'f833', 'f834', 'f835', 'f836', 'f837', 'f838', 'f839', 'f840', 'f841', 'f842', 'f843', 'f844', 'f845', 'f846', 'f847', 'f848', 'f849', 'f850', 'f851', 'f852', 'f853', 'f854', 'f855', 'f856', 'f857', 'f858', 'f859', 'f860', 'f861', 'f862', 'f863', 'f864', 'f865', 'f866', 'f867', 'f868', 'f869', 'f870', 'f871', 'f872', 'f873', 'f874', 'f875', 'f876', 'f877', 'f878', 'f879', 'f880', 'f881', 'f882', 'f883', 'f884', 'f885', 'f886', 'f887', 'f888', 'f889', 'f890', 'f891', 'f892', 'f893', 'f894', 'f895', 'f896', 'f897', 'f898', 'f899', 'f900', 'f901', 'f902', 'f903', 'f904', 'f905', 'f906', 'f907', 'f908', 'f909', 'f910', 'f911', 'f912', 'f913', 'f914', 'f915', 'f916', 'f917', 'f918', 'f919', 'f920', 'f921', 'f922', 'f923', 'f924', 'f925', 'f926', 'f927', 'f928', 'f929', 'f930', 'f931', 'f932', 'f933', 'f934', 'f935', 'f936', 'f937', 'f938', 'f939', 'f940', 'f941', 'f942', 'f943', 'f944', 'f945', 'f946', 'f947', 'f948', 'f949', 'f950', 'f951', 'f952', 'f953', 'f954', 'f955', 'f956', 'f957', 'f958', 'f959', 'f960', 'f961', 'f962', 'f963', 'f964', 'f965', 'f966', 'f967', 'f968', 'f969', 'f970', 'f971', 'f972', 'f973', 'f974', 'f975', 'f976', 'f977', 'f978', 'f979', 'f980', 'f981', 'f982', 'f983', 'f984', 'f985', 'f986', 'f987', 'f988', 'f989', 'f990', 'f991', 'f992', 'f993', 'f994', 'f995', 'f996', 'f997', 'f998', 'f999', 'f1000', 'f1001', 'f1002', 'f1003', 'f1004', 'f1005', 'f1006', 'f1007', 'f1008', 'f1009', 'f1010', 'f1011', 'f1012', 'f1013', 'f1014', 'f1015', 'f1016', 'f1017', 'f1018', 'f1019', 'f1020', 'f1021', 'f1022', 'f1023', 'f1024', 'f1025', 'f1026', 'f1027', 'f1028', 'f1029', 'f1030', 'f1031', 'f1032', 'f1033', 'f1034', 'f1035', 'f1036', 'f1037', 'f1038', 'f1039', 'f1040', 'f1041', 'f1042', 'f1043', 'f1044', 'f1045', 'f1046', 'f1047', 'f1048', 'f1049', 'f1050', 'f1051', 'f1052', 'f1053', 'f1054', 'f1055', 'f1056', 'f1057', 'f1058', 'f1059', 'f1060', 'f1061', 'f1062', 'f1063', 'f1064', 'f1065', 'f1066', 'f1067', 'f1068', 'f1069', 'f1070', 'f1071', 'f1072', 'f1073', 'f1074', 'f1075', 'f1076', 'f1077', 'f1078', 'f1079', 'f1080', 'f1081', 'f1082', 'f1083', 'f1084', 'f1085', 'f1086', 'f1087', 'f1088', 'f1089', 'f1090', 'f1091', 'f1092', 'f1093', 'f1094', 'f1095', 'f1096', 'f1097', 'f1098', 'f1099', 'f1100', 'f1101', 'f1102', 'f1103', 'f1104', 'f1105', 'f1106', 'f1107', 'f1108', 'f1109', 'f1110', 'f1111', 'f1112', 'f1113', 'f1114', 'f1115', 'f1116', 'f1117', 'f1118', 'f1119', 'f1120', 'f1121', 'f1122', 'f1123', 'f1124', 'f1125', 'f1126', 'f1127', 'f1128', 'f1129', 'f1130', 'f1131', 'f1132', 'f1133', 'f1134', 'f1135', 'f1136', 'f1137', 'f1138', 'f1139', 'f1140', 'f1141', 'f1142', 'f1143', 'f1144', 'f1145', 'f1146', 'f1147', 'f1148', 'f1149', 'f1150', 'f1151', 'f1152', 'f1153', 'f1154', 'f1155', 'f1156', 'f1157', 'f1158', 'f1159', 'f1160', 'f1161', 'f1162', 'f1163', 'f1164', 'f1165', 'f1166', 'f1167', 'f1168', 'f1169', 'f1170', 'f1171', 'f1172', 'f1173', 'f1174', 'f1175', 'f1176', 'f1177', 'f1178', 'f1179', 'f1180', 'f1181', 'f1182', 'f1183', 'f1184', 'f1185', 'f1186', 'f1187', 'f1188', 'f1189', 'f1190', 'f1191', 'f1192', 'f1193', 'f1194', 'f1195', 'f1196', 'f1197', 'f1198', 'f1199', 'f1200', 'f1201', 'f1202', 'f1203', 'f1204', 'f1205', 'f1206', 'f1207', 'f1208', 'f1209', 'f1210', 'f1211', 'f1212', 'f1213', 'f1214', 'f1215', 'f1216', 'f1217', 'f1218', 'f1219', 'f1220', 'f1221', 'f1222', 'f1223', 'f1224', 'f1225', 'f1226', 'f1227', 'f1228', 'f1229', 'f1230', 'f1231', 'f1232', 'f1233', 'f1234', 'f1235', 'f1236', 'f1237', 'f1238', 'f1239', 'f1240', 'f1241', 'f1242', 'f1243', 'f1244', 'f1245', 'f1246', 'f1247', 'f1248', 'f1249', 'f1250', 'f1251', 'f1252', 'f1253', 'f1254', 'f1255', 'f1256', 'f1257', 'f1258', 'f1259', 'f1260', 'f1261', 'f1262', 'f1263', 'f1264', 'f1265', 'f1266', 'f1267', 'f1268', 'f1269', 'f1270', 'f1271', 'f1272', 'f1273', 'f1274', 'f1275', 'f1276', 'f1277', 'f1278', 'f1279', 'f1280', 'f1281', 'f1282', 'f1283', 'f1284', 'f1285', 'f1286', 'f1287', 'f1288', 'f1289', 'f1290', 'f1291', 'f1292', 'f1293', 'f1294', 'f1295', 'f1296', 'f1297', 'f1298', 'f1299', 'f1300', 'f1301', 'f1302', 'f1303', 'f1304', 'f1305', 'f1306', 'f1307', 'f1308', 'f1309', 'f1310', 'f1311', 'f1312', 'f1313', 'f1314', 'f1315', 'f1316', 'f1317', 'f1318', 'f1319', 'f1320', 'f1321', 'f1322', 'f1323', 'f1324', 'f1325', 'f1326', 'f1327', 'f1328', 'f1329', 'f1330', 'f1331', 'f1332', 'f1333', 'f1334', 'f1335', 'f1336', 'f1337', 'f1338', 'f1339', 'f1340', 'f1341', 'f1342', 'f1343', 'f1344', 'f1345', 'f1346', 'f1347', 'f1348', 'f1349', 'f1350', 'f1351', 'f1352', 'f1353', 'f1354', 'f1355', 'f1356', 'f1357', 'f1358', 'f1359', 'f1360', 'f1361', 'f1362', 'f1363', 'f1364', 'f1365', 'f1366', 'f1367', 'f1368', 'f1369', 'f1370', 'f1371', 'f1372', 'f1373', 'f1374', 'f1375', 'f1376', 'f1377', 'f1378', 'f1379', 'f1380', 'f1381', 'f1382', 'f1383', 'f1384', 'f1385', 'f1386', 'f1387', 'f1388', 'f1389', 'f1390', 'f1391', 'f1392', 'f1393', 'f1394', 'f1395', 'f1396', 'f1397', 'f1398', 'f1399', 'f1400', 'f1401', 'f1402', 'f1403', 'f1404', 'f1405', 'f1406', 'f1407', 'f1408', 'f1409', 'f1410', 'f1411', 'f1412', 'f1413', 'f1414', 'f1415', 'f1416', 'f1417', 'f1418', 'f1419', 'f1420', 'f1421', 'f1422', 'f1423', 'f1424', 'f1425', 'f1426', 'f1427', 'f1428', 'f1429', 'f1430', 'f1431', 'f1432', 'f1433', 'f1434', 'f1435', 'f1436', 'f1437', 'f1438', 'f1439', 'f1440', 'f1441', 'f1442', 'f1443', 'f1444', 'f1445', 'f1446', 'f1447', 'f1448', 'f1449', 'f1450', 'f1451', 'f1452', 'f1453', 'f1454', 'f1455', 'f1456', 'f1457', 'f1458', 'f1459', 'f1460', 'f1461', 'f1462', 'f1463', 'f1464', 'f1465', 'f1466', 'f1467', 'f1468', 'f1469', 'f1470', 'f1471', 'f1472', 'f1473', 'f1474', 'f1475', 'f1476', 'f1477', 'f1478', 'f1479', 'f1480', 'f1481', 'f1482', 'f1483', 'f1484', 'f1485', 'f1486', 'f1487', 'f1488', 'f1489', 'f1490', 'f1491', 'f1492', 'f1493', 'f1494', 'f1495', 'f1496', 'f1497', 'f1498', 'f1499', 'f1500', 'f1501', 'f1502', 'f1503', 'f1504', 'f1505', 'f1506', 'f1507', 'f1508', 'f1509', 'f1510', 'f1511', 'f1512', 'f1513', 'f1514', 'f1515', 'f1516', 'f1517', 'f1518', 'f1519', 'f1520', 'f1521', 'f1522', 'f1523', 'f1524', 'f1525', 'f1526', 'f1527', 'f1528', 'f1529', 'f1530', 'f1531', 'f1532', 'f1533', 'f1534', 'f1535', 'f1536', 'f1537', 'f1538', 'f1539', 'f1540', 'f1541', 'f1542', 'f1543', 'f1544', 'f1545', 'f1546', 'f1547', 'f1548', 'f1549', 'f1550', 'f1551', 'f1552', 'f1553', 'f1554', 'f1555', 'f1556', 'f1557', 'f1558', 'f1559', 'f1560', 'f1561', 'f1562', 'f1563', 'f1564', 'f1565', 'f1566', 'f1567', 'f1568', 'f1569', 'f1570', 'f1571', 'f1572', 'f1573', 'f1574', 'f1575', 'f1576', 'f1577', 'f1578', 'f1579', 'f1580', 'f1581', 'f1582', 'f1583', 'f1584', 'f1585', 'f1586', 'f1587', 'f1588', 'f1589', 'f1590', 'f1591', 'f1592', 'f1593', 'f1594', 'f1595', 'f1596', 'f1597', 'f1598', 'f1599', 'f1600', 'f1601', 'f1602', 'f1603', 'f1604', 'f1605', 'f1606', 'f1607', 'f1608', 'f1609', 'f1610', 'f1611', 'f1612', 'f1613', 'f1614', 'f1615', 'f1616', 'f1617', 'f1618', 'f1619', 'f1620', 'f1621', 'f1622', 'f1623', 'f1624', 'f1625', 'f1626', 'f1627', 'f1628', 'f1629', 'f1630', 'f1631', 'f1632', 'f1633', 'f1634', 'f1635', 'f1636', 'f1637', 'f1638', 'f1639', 'f1640', 'f1641', 'f1642', 'f1643', 'f1644', 'f1645', 'f1646', 'f1647', 'f1648', 'f1649', 'f1650', 'f1651', 'f1652', 'f1653', 'f1654', 'f1655', 'f1656', 'f1657', 'f1658', 'f1659', 'f1660', 'f1661', 'f1662', 'f1663', 'f1664', 'f1665', 'f1666', 'f1667', 'f1668', 'f1669', 'f1670', 'f1671', 'f1672', 'f1673', 'f1674', 'f1675', 'f1676', 'f1677', 'f1678', 'f1679', 'f1680', 'f1681', 'f1682', 'f1683', 'f1684', 'f1685', 'f1686', 'f1687', 'f1688', 'f1689', 'f1690', 'f1691', 'f1692', 'f1693', 'f1694', 'f1695', 'f1696', 'f1697', 'f1698', 'f1699', 'f1700', 'f1701', 'f1702', 'f1703', 'f1704', 'f1705', 'f1706', 'f1707', 'f1708', 'f1709', 'f1710', 'f1711', 'f1712', 'f1713', 'f1714', 'f1715', 'f1716', 'f1717', 'f1718', 'f1719', 'f1720', 'f1721', 'f1722', 'f1723', 'f1724', 'f1725', 'f1726', 'f1727', 'f1728', 'f1729', 'f1730', 'f1731', 'f1732', 'f1733', 'f1734', 'f1735', 'f1736', 'f1737', 'f1738', 'f1739', 'f1740', 'f1741', 'f1742', 'f1743', 'f1744', 'f1745', 'f1746', 'f1747', 'f1748', 'f1749', 'f1750', 'f1751', 'f1752', 'f1753', 'f1754', 'f1755', 'f1756', 'f1757', 'f1758', 'f1759', 'f1760', 'f1761', 'f1762', 'f1763', 'f1764', 'f1765', 'f1766', 'f1767', 'f1768', 'f1769', 'f1770', 'f1771', 'f1772', 'f1773', 'f1774', 'f1775', 'f1776', 'f1777', 'f1778', 'f1779', 'f1780', 'f1781', 'f1782', 'f1783', 'f1784', 'f1785', 'f1786', 'f1787', 'f1788', 'f1789', 'f1790', 'f1791', 'f1792', 'f1793', 'f1794', 'f1795', 'f1796', 'f1797', 'f1798', 'f1799', 'f1800', 'f1801', 'f1802', 'f1803', 'f1804', 'f1805', 'f1806', 'f1807', 'f1808', 'f1809', 'f1810', 'f1811', 'f1812', 'f1813', 'f1814', 'f1815', 'f1816', 'f1817', 'f1818', 'f1819', 'f1820', 'f1821', 'f1822', 'f1823', 'f1824', 'f1825', 'f1826', 'f1827', 'f1828', 'f1829', 'f1830', 'f1831', 'f1832', 'f1833', 'f1834', 'f1835', 'f1836', 'f1837', 'f1838', 'f1839', 'f1840', 'f1841', 'f1842', 'f1843', 'f1844', 'f1845', 'f1846', 'f1847', 'f1848', 'f1849', 'f1850', 'f1851', 'f1852', 'f1853', 'f1854', 'f1855', 'f1856', 'f1857', 'f1858', 'f1859', 'f1860', 'f1861', 'f1862', 'f1863', 'f1864', 'f1865', 'f1866', 'f1867', 'f1868', 'f1869', 'f1870', 'f1871', 'f1872', 'f1873', 'f1874', 'f1875', 'f1876', 'f1877', 'f1878', 'f1879', 'f1880', 'f1881', 'f1882', 'f1883', 'f1884', 'f1885', 'f1886', 'f1887', 'f1888', 'f1889', 'f1890', 'f1891', 'f1892', 'f1893', 'f1894', 'f1895', 'f1896', 'f1897', 'f1898', 'f1899', 'f1900', 'f1901', 'f1902', 'f1903', 'f1904', 'f1905', 'f1906', 'f1907', 'f1908', 'f1909', 'f1910', 'f1911', 'f1912', 'f1913', 'f1914', 'f1915', 'f1916', 'f1917', 'f1918', 'f1919', 'f1920', 'f1921', 'f1922', 'f1923', 'f1924', 'f1925', 'f1926', 'f1927', 'f1928', 'f1929', 'f1930', 'f1931', 'f1932', 'f1933', 'f1934', 'f1935', 'f1936', 'f1937', 'f1938', 'f1939', 'f1940', 'f1941', 'f1942', 'f1943', 'f1944', 'f1945', 'f1946', 'f1947', 'f1948', 'f1949', 'f1950', 'f1951', 'f1952', 'f1953', 'f1954', 'f1955', 'f1956', 'f1957', 'f1958', 'f1959', 'f1960', 'f1961', 'f1962', 'f1963', 'f1964', 'f1965', 'f1966', 'f1967', 'f1968', 'f1969', 'f1970', 'f1971', 'f1972', 'f1973', 'f1974', 'f1975', 'f1976', 'f1977', 'f1978', 'f1979', 'f1980', 'f1981', 'f1982', 'f1983', 'f1984', 'f1985', 'f1986', 'f1987', 'f1988', 'f1989', 'f1990', 'f1991', 'f1992', 'f1993', 'f1994', 'f1995', 'f1996', 'f1997', 'f1998', 'f1999', 'f2000', 'f2001', 'f2002', 'f2003', 'f2004', 'f2005', 'f2006', 'f2007', 'f2008', 'f2009', 'f2010', 'f2011', 'f2012', 'f2013', 'f2014', 'f2015', 'f2016', 'f2017', 'f2018', 'f2019', 'f2020', 'f2021', 'f2022', 'f2023', 'f2024', 'f2025', 'f2026', 'f2027', 'f2028', 'f2029', 'f2030', 'f2031', 'f2032', 'f2033', 'f2034', 'f2035', 'f2036', 'f2037', 'f2038', 'f2039', 'f2040', 'f2041', 'f2042', 'f2043', 'f2044', 'f2045', 'f2046', 'f2047', 'f2048', 'f2049', 'f2050', 'f2051', 'f2052', 'f2053', 'f2054', 'f2055', 'f2056', 'f2057', 'f2058', 'f2059', 'f2060', 'f2061', 'f2062', 'f2063', 'f2064', 'f2065', 'f2066', 'f2067', 'f2068', 'f2069', 'f2070', 'f2071', 'f2072', 'f2073', 'f2074', 'f2075', 'f2076', 'f2077', 'f2078', 'f2079', 'f2080', 'f2081', 'f2082', 'f2083', 'f2084', 'f2085', 'f2086', 'f2087', 'f2088', 'f2089', 'f2090', 'f2091', 'f2092', 'f2093', 'f2094', 'f2095', 'f2096', 'f2097', 'f2098', 'f2099', 'f2100', 'f2101', 'f2102', 'f2103', 'f2104', 'f2105', 'f2106', 'f2107', 'f2108', 'f2109', 'f2110', 'f2111', 'f2112', 'f2113', 'f2114', 'f2115', 'f2116', 'f2117', 'f2118', 'f2119', 'f2120', 'f2121', 'f2122', 'f2123', 'f2124', 'f2125', 'f2126', 'f2127', 'f2128', 'f2129', 'f2130', 'f2131', 'f2132', 'f2133', 'f2134', 'f2135', 'f2136', 'f2137', 'f2138', 'f2139', 'f2140', 'f2141', 'f2142', 'f2143', 'f2144', 'f2145', 'f2146', 'f2147', 'f2148', 'f2149', 'f2150', 'f2151', 'f2152', 'f2153', 'f2154', 'f2155', 'f2156', 'f2157', 'f2158', 'f2159', 'f2160', 'f2161', 'f2162', 'f2163', 'f2164', 'f2165', 'f2166', 'f2167', 'f2168', 'f2169', 'f2170', 'f2171', 'f2172', 'f2173', 'f2174', 'f2175', 'f2176', 'f2177', 'f2178', 'f2179', 'f2180', 'f2181', 'f2182', 'f2183', 'f2184', 'f2185', 'f2186', 'f2187', 'f2188', 'f2189', 'f2190', 'f2191', 'f2192', 'f2193', 'f2194', 'f2195', 'f2196', 'f2197', 'f2198', 'f2199', 'f2200', 'f2201', 'f2202', 'f2203', 'f2204', 'f2205', 'f2206', 'f2207', 'f2208', 'f2209', 'f2210', 'f2211', 'f2212', 'f2213', 'f2214', 'f2215', 'f2216', 'f2217', 'f2218', 'f2219', 'f2220', 'f2221', 'f2222', 'f2223', 'f2224', 'f2225', 'f2226', 'f2227', 'f2228', 'f2229', 'f2230', 'f2231', 'f2232', 'f2233', 'f2234', 'f2235', 'f2236', 'f2237', 'f2238', 'f2239', 'f2240', 'f2241', 'f2242', 'f2243', 'f2244', 'f2245', 'f2246', 'f2247', 'f2248', 'f2249', 'f2250', 'f2251', 'f2252', 'f2253', 'f2254', 'f2255', 'f2256', 'f2257', 'f2258', 'f2259', 'f2260', 'f2261', 'f2262', 'f2263', 'f2264', 'f2265', 'f2266', 'f2267', 'f2268', 'f2269', 'f2270', 'f2271', 'f2272', 'f2273', 'f2274', 'f2275', 'f2276', 'f2277', 'f2278', 'f2279', 'f2280', 'f2281', 'f2282', 'f2283', 'f2284', 'f2285', 'f2286', 'f2287', 'f2288', 'f2289', 'f2290', 'f2291', 'f2292', 'f2293', 'f2294', 'f2295', 'f2296', 'f2297', 'f2298', 'f2299', 'f2300', 'f2301', 'f2302', 'f2303', 'f2304', 'f2305', 'f2306', 'f2307', 'f2308', 'f2309', 'f2310', 'f2311', 'f2312', 'f2313', 'f2314', 'f2315', 'f2316', 'f2317', 'f2318', 'f2319', 'f2320', 'f2321', 'f2322', 'f2323', 'f2324', 'f2325', 'f2326', 'f2327', 'f2328', 'f2329', 'f2330', 'f2331', 'f2332', 'f2333', 'f2334', 'f2335', 'f2336', 'f2337', 'f2338', 'f2339', 'f2340', 'f2341', 'f2342', 'f2343', 'f2344', 'f2345', 'f2346', 'f2347', 'f2348', 'f2349', 'f2350', 'f2351', 'f2352', 'f2353', 'f2354', 'f2355', 'f2356', 'f2357', 'f2358', 'f2359', 'f2360', 'f2361', 'f2362', 'f2363', 'f2364', 'f2365', 'f2366', 'f2367', 'f2368', 'f2369', 'f2370', 'f2371', 'f2372', 'f2373', 'f2374', 'f2375']\n",
      "expected f2394, f2379, f2382, f2377, f2389, f2396, f2397, f2386, f2392, f2381, f2393, f2388, f2390, f2378, f2383, f2387, f2385, f2380, f2391, f2384, f2376, f2395 in input data\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:55:32,259:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 140. configuration. Duration: 4.101027; loss: 2.000000; status 3; additional run info:  \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:55:32,332:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:55:32,407:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:55:32,560:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 114 training points for SMAC.\n",
      "[INFO] [2016-08-16 07:55:34,882:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.377049 14: 0.377049 15: 0.377049 16: 0.377049 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.381148 32: 0.385246 33: 0.385246 34: 0.385246 35: 0.385246 36: 0.389344 37: 0.389344 38: 0.389344 39: 0.389344 40: 0.385246 41: 0.385246 42: 0.385246 43: 0.385246 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [25, 11, 18, 4, 11, 11, 2, 2, 2, 2, 2, 2, 2, 11, 11, 2, 2, 2, 2, 2, 2, 2, 2, 2, 24, 2, 2, 2, 2, 2, 7, 7, 11, 2, 2, 2, 2, 2, 2, 2, 11, 2, 2, 2, 11, 2, 2, 2, 2, 2]\n",
      "\tWeights: [ 0.    0.    0.72  0.    0.02  0.    0.    0.04  0.    0.    0.    0.16\n",
      "  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.\n",
      "  0.02  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 14) (1, 21) (1, 31) (1, 40) (1, 63) (1, 73) (1, 79)\n",
      "[INFO] [2016-08-16 07:55:34,891:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:55:34,894:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.566944 seconds\n",
      "[INFO] [2016-08-16 07:55:34,896:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:55:55,631:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 23.0681 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:55:55,640:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 141. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:55,642:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 3\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.102161965068\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:56,816:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 141. configuration. Duration: 1.099840; loss: 0.659836; status 1; additional run info: ;duration: 1.099839687347412;num_run:00141 \n",
      "[INFO] [2016-08-16 07:55:56,827:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 142. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:56,830:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: True\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 2.45719278424\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 16\n",
      "  classifier:extra_trees:min_samples_split, Value: 3\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 17\n",
      "  preprocessor:gem:precond, Value: 0.436169002639\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:55:57,042:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:55:57,207:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:55:57,370:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 142. configuration. Duration: 0.478962; loss: 0.721311; status 1; additional run info: ;duration: 0.4789619445800781;num_run:00142 \n",
      "[INFO] [2016-08-16 07:55:57,381:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 143. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:57,384:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 6\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:58,396:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 143. configuration. Duration: 0.922374; loss: 0.651639; status 1; additional run info: ;duration: 0.9223735332489014;num_run:00143 \n",
      "[INFO] [2016-08-16 07:55:58,407:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 144. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:58,409:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 0.0673868626678\n",
      "  classifier:bernoulli_nb:fit_prior, Value: True\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000108475751982\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 10\n",
      "  preprocessor:gem:precond, Value: 0.0268437276948\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:58,560:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 144. configuration. Duration: 0.054932; loss: 0.778689; status 1; additional run info: ;duration: 0.054931640625;num_run:00144 \n",
      "[INFO] [2016-08-16 07:55:58,572:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 145. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:58,575:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 6\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.345646237116\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:59,494:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 145. configuration. Duration: 0.846189; loss: 0.651639; status 1; additional run info: ;duration: 0.8461892604827881;num_run:00145 \n",
      "[INFO] [2016-08-16 07:55:59,505:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 146. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:59,507:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 1.00093316056e-05\n",
      "  classifier:sgd:average, Value: False\n",
      "  classifier:sgd:eta0, Value: 0.0326282800531\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: invscaling\n",
      "  classifier:sgd:loss, Value: perceptron\n",
      "  classifier:sgd:n_iter, Value: 6\n",
      "  classifier:sgd:penalty, Value: l2\n",
      "  classifier:sgd:power_t, Value: 0.386306851624\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0420798829914\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:55:59,594:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 146. configuration. Duration: 0.038296; loss: 0.930328; status 1; additional run info: ;duration: 0.03829646110534668;num_run:00146 \n",
      "[INFO] [2016-08-16 07:55:59,605:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 147. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:55:59,608:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.1\n",
      "  classifier:adaboost:max_depth, Value: 1\n",
      "  classifier:adaboost:n_estimators, Value: 50\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 10\n",
      "  preprocessor:gem:precond, Value: 0.1\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:56:00,073:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 147. configuration. Duration: 0.401770; loss: 0.692623; status 1; additional run info: ;duration: 0.40176963806152344;num_run:00147 \n",
      "[INFO] [2016-08-16 07:56:00,086:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 148. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:00,089:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: qda\n",
      "  classifier:qda:reg_param, Value: 5.38617674192\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0335017435815\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: nystroem_sampler\n",
      "  preprocessor:nystroem_sampler:coef0, Value: -0.56547115424\n",
      "  preprocessor:nystroem_sampler:gamma, Value: 5.66906760778\n",
      "  preprocessor:nystroem_sampler:kernel, Value: sigmoid\n",
      "  preprocessor:nystroem_sampler:n_components, Value: 2150\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/kernel_approximation.py:463: UserWarning: n_components > n_samples. This is not possible.\n",
      "n_components was set to n_samples, which results in inefficient evaluation of the full kernel.\n",
      "  warnings.warn(\"n_components > n_samples. This is not possible.\\n\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:00,997:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.385246 7: 0.381148 8: 0.381148 9: 0.377049 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.377049 14: 0.377049 15: 0.377049 16: 0.377049 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.372951 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.381148 32: 0.385246 33: 0.385246 34: 0.385246 35: 0.385246 36: 0.389344 37: 0.389344 38: 0.389344 39: 0.389344 40: 0.385246 41: 0.385246 42: 0.385246 43: 0.385246 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [24, 10, 17, 3, 10, 10, 1, 1, 1, 1, 1, 1, 1, 10, 10, 1, 1, 1, 1, 1, 1, 1, 1, 1, 23, 1, 1, 1, 1, 1, 6, 6, 10, 1, 1, 1, 1, 1, 1, 1, 10, 1, 1, 1, 10, 1, 1, 1, 1, 1]\n",
      "\tWeights: [ 0.    0.72  0.    0.02  0.    0.    0.04  0.    0.    0.    0.16  0.    0.\n",
      "  0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.    0.02  0.02\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 14) (1, 21) (1, 31) (1, 40) (1, 63) (1, 73) (1, 79)\n",
      "[INFO] [2016-08-16 07:56:01,020:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:56:01,053:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 4.020052 seconds\n",
      "[INFO] [2016-08-16 07:56:01,063:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/discriminant_analysis.py:688: UserWarning: Variables are collinear\n",
      "  warnings.warn(\"Variables are collinear\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:01,916:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 148. configuration. Duration: 1.652377; loss: 0.856557; status 1; additional run info: ;duration: 1.652376651763916;num_run:00148 \n",
      "[INFO] [2016-08-16 07:56:01,937:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 149. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:01,943:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.1\n",
      "  classifier:adaboost:max_depth, Value: 1\n",
      "  classifier:adaboost:n_estimators, Value: 50\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.193390083915\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:56:02,298:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 149. configuration. Duration: 0.263699; loss: 0.663934; status 1; additional run info: ;duration: 0.2636992931365967;num_run:00149 \n",
      "[INFO] [2016-08-16 07:56:02,316:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 150. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:02,320:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 3.23971584618\n",
      "  classifier:bernoulli_nb:fit_prior, Value: True\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.292882349526\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.350242476976\n",
      "  preprocessor:select_rates:mode, Value: fdr\n",
      "  preprocessor:select_rates:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:02,410:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 150. configuration. Duration: 0.031575; loss: 0.872951; status 1; additional run info: ;duration: 0.03157520294189453;num_run:00150 \n",
      "[INFO] [2016-08-16 07:56:02,424:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 151. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:02,429:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.1\n",
      "  classifier:adaboost:max_depth, Value: 1\n",
      "  classifier:adaboost:n_estimators, Value: 50\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00031942807827\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: euclidean\n",
      "  preprocessor:feature_agglomeration:linkage, Value: ward\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 25\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: mean\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:56:02,680:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 151. configuration. Duration: 0.184323; loss: 0.663934; status 1; additional run info: ;duration: 0.18432283401489258;num_run:00151 \n",
      "[INFO] [2016-08-16 07:56:02,694:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 152. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:02,698:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: qda\n",
      "  classifier:qda:reg_param, Value: 7.7447270459\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 65.4871140355\n",
      "  preprocessor:select_percentile_classification:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:56:02,795:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 152. configuration. Duration: 0.037527; loss: 0.831967; status 1; additional run info: ;duration: 0.03752732276916504;num_run:00152 \n",
      "[INFO] [2016-08-16 07:56:02,807:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 153. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:02,810:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.1\n",
      "  classifier:adaboost:max_depth, Value: 1\n",
      "  classifier:adaboost:n_estimators, Value: 50\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.099038041764\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: euclidean\n",
      "  preprocessor:feature_agglomeration:linkage, Value: ward\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 25\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: mean\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:56:03,077:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 153. configuration. Duration: 0.200906; loss: 0.663934; status 1; additional run info: ;duration: 0.20090603828430176;num_run:00153 \n",
      "[INFO] [2016-08-16 07:56:03,092:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 154. configuration (from SMAC) with time limit 360s.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:03,096:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: entropy\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 4.79774405878\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 11\n",
      "  classifier:extra_trees:min_samples_split, Value: 18\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000111418221433\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:gamma, Value: 0.0191105526929\n",
      "  preprocessor:kernel_pca:kernel, Value: rbf\n",
      "  preprocessor:kernel_pca:n_components, Value: 106\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[ERROR] [2016-08-16 07:56:03,109:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:56:03,261:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:56:04,242:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 154. configuration. Duration: 0.999073; loss: 0.750000; status 1; additional run info: ;duration: 0.9990730285644531;num_run:00154 \n",
      "[INFO] [2016-08-16 07:56:04,255:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 155. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:04,260:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.0715608529004\n",
      "  classifier:adaboost:max_depth, Value: 10\n",
      "  classifier:adaboost:n_estimators, Value: 444\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: cosine\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 388\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: mean\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:56:07,853:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 155. configuration. Duration: 3.438564; loss: 0.774590; status 1; additional run info: ;duration: 3.438563823699951;num_run:00155 \n",
      "[INFO] [2016-08-16 07:56:07,868:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 156. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:07,871:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: entropy\n",
      "  classifier:decision_tree:max_depth, Value: 0.301538668998\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 2\n",
      "  classifier:decision_tree:min_samples_split, Value: 12\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000275256352782\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: liblinear_svc_preprocessor\n",
      "  preprocessor:liblinear_svc_preprocessor:C, Value: 258.969125453\n",
      "  preprocessor:liblinear_svc_preprocessor:dual, Constant: False\n",
      "  preprocessor:liblinear_svc_preprocessor:fit_intercept, Constant: True\n",
      "  preprocessor:liblinear_svc_preprocessor:intercept_scaling, Constant: 1\n",
      "  preprocessor:liblinear_svc_preprocessor:loss, Value: squared_hinge\n",
      "  preprocessor:liblinear_svc_preprocessor:multi_class, Constant: ovr\n",
      "  preprocessor:liblinear_svc_preprocessor:penalty, Constant: l1\n",
      "  preprocessor:liblinear_svc_preprocessor:tol, Value: 0.000234836662375\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:56:08,048:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.381148 7: 0.377049 8: 0.377049 9: 0.381148 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.377049 14: 0.377049 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.385246 19: 0.381148 20: 0.377049 21: 0.377049 22: 0.377049 23: 0.377049 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.385246 28: 0.385246 29: 0.385246 30: 0.385246 31: 0.385246 32: 0.385246 33: 0.381148 34: 0.385246 35: 0.385246 36: 0.385246 37: 0.385246 38: 0.381148 39: 0.381148 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.377049 47: 0.377049 48: 0.381148 49: 0.381148\n",
      "\tMembers: [21, 7, 14, 2, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 6, 2, 3, 6, 2, 6, 7, 7, 3, 2, 1, 14, 7, 7, 7, 7, 7, 20, 47, 7, 7, 7, 6, 7, 7, 7, 7, 7, 7, 7, 3, 2, 6, 7]\n",
      "\tWeights: [ 0.    0.02  0.1   0.06  0.    0.    0.1   0.62  0.    0.    0.    0.    0.\n",
      "  0.    0.04  0.    0.    0.    0.    0.    0.02  0.02  0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.  ]\n",
      "\tIdentifiers: (1, 19) (1, 21) (1, 31) (1, 39) (1, 40) (1, 63) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:56:08,060:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:56:08,064:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 4.965663 seconds\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:08,071:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (148)!.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:08,074:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (148)!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:56:08,097:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:56:08,133:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 156. configuration. Duration: 0.201516; loss: 0.745902; status 1; additional run info: ;duration: 0.20151591300964355;num_run:00156 \n",
      "[INFO] [2016-08-16 07:56:08,146:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 157. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:08,152:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.1\n",
      "  classifier:adaboost:max_depth, Value: 1\n",
      "  classifier:adaboost:n_estimators, Value: 50\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0822641305677\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: deflation\n",
      "  preprocessor:fast_ica:fun, Value: exp\n",
      "  preprocessor:fast_ica:n_components, Value: 457\n",
      "  preprocessor:fast_ica:whiten, Value: True\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "n_components is too large: it will be set to 9\n",
      "[ERROR] [2016-08-16 07:56:08,231:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:56:08,511:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 157. configuration. Duration: 0.289022; loss: 0.709016; status 1; additional run info: ;duration: 0.28902196884155273;num_run:00157 \n",
      "[INFO] [2016-08-16 07:56:08,525:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 158. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:08,529:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 2.31872587345\n",
      "  classifier:bernoulli_nb:fit_prior, Value: True\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.155574273535\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: nystroem_sampler\n",
      "  preprocessor:nystroem_sampler:gamma, Value: 0.00377270364971\n",
      "  preprocessor:nystroem_sampler:kernel, Value: rbf\n",
      "  preprocessor:nystroem_sampler:n_components, Value: 7416\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/kernel_approximation.py:463: UserWarning: n_components > n_samples. This is not possible.\n",
      "n_components was set to n_samples, which results in inefficient evaluation of the full kernel.\n",
      "  warnings.warn(\"n_components > n_samples. This is not possible.\\n\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:10,224:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 158. configuration. Duration: 1.546302; loss: 0.856557; status 1; additional run info: ;duration: 1.546302318572998;num_run:00158 \n",
      "[INFO] [2016-08-16 07:56:10,237:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 159. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:10,240:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.525298023193\n",
      "  classifier:adaboost:max_depth, Value: 6\n",
      "  classifier:adaboost:n_estimators, Value: 168\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: euclidean\n",
      "  preprocessor:feature_agglomeration:linkage, Value: ward\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 275\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: max\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:11,047:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 159. configuration. Duration: 0.718596; loss: 0.774590; status 1; additional run info: ;duration: 0.7185957431793213;num_run:00159 \n",
      "[INFO] [2016-08-16 07:56:11,061:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 160. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:11,067:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 0.000247072542735\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 285\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000172684354075\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: manhattan\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 179\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: max\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:56:11,905:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 160. configuration. Duration: 0.753995; loss: 0.803279; status 1; additional run info: ;duration: 0.7539947032928467;num_run:00160 \n",
      "[INFO] [2016-08-16 07:56:11,926:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 161. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:11,932:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0102608574057\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 9\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 14\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 419\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.0299535003052\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 8\n",
      "  preprocessor:gem:precond, Value: 0.475489481424\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:56:12,945:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 161. configuration. Duration: 0.903133; loss: 0.860656; status 1; additional run info: ;duration: 0.9031331539154053;num_run:00161 \n",
      "[INFO] [2016-08-16 07:56:12,960:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 162. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:12,963:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: proj_logit\n",
      "  classifier:proj_logit:max_epochs, Value: 5\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0395011824554\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 1.84792585156\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 1659\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:14,237:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.381148 7: 0.377049 8: 0.377049 9: 0.381148 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.377049 14: 0.377049 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.385246 19: 0.381148 20: 0.377049 21: 0.377049 22: 0.377049 23: 0.377049 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.385246 28: 0.385246 29: 0.385246 30: 0.385246 31: 0.385246 32: 0.385246 33: 0.381148 34: 0.385246 35: 0.385246 36: 0.385246 37: 0.385246 38: 0.381148 39: 0.381148 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.377049 47: 0.377049 48: 0.381148 49: 0.381148\n",
      "\tMembers: [21, 7, 14, 2, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 6, 2, 3, 6, 2, 6, 7, 7, 3, 2, 1, 14, 7, 7, 7, 7, 7, 20, 47, 7, 7, 7, 6, 7, 7, 7, 7, 7, 7, 7, 3, 2, 6, 7]\n",
      "\tWeights: [ 0.    0.02  0.1   0.06  0.    0.    0.1   0.62  0.    0.    0.    0.    0.\n",
      "  0.    0.04  0.    0.    0.    0.    0.    0.02  0.02  0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.  ]\n",
      "\tIdentifiers: (1, 19) (1, 21) (1, 31) (1, 39) (1, 40) (1, 63) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:56:14,260:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:56:14,272:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 6.184266 seconds\n",
      "[INFO] [2016-08-16 07:56:14,277:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run16\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:56:16,367:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:56:16,775:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:56:17,622:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 162. configuration. Duration: 4.596748; loss: 0.877049; status 1; additional run info: ;duration: 4.596747636795044;num_run:00162 \n",
      "[INFO] [2016-08-16 07:56:17,636:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 163. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:17,641:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0333938834612\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 1\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 13\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 176\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.880926669034\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.194565211102\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: deflation\n",
      "  preprocessor:fast_ica:fun, Value: exp\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:56:18,086:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 163. configuration. Duration: 0.379196; loss: 0.737705; status 1; additional run info: ;duration: 0.3791956901550293;num_run:00163 \n",
      "[INFO] [2016-08-16 07:56:18,101:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 164. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:18,105:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0234978864833\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 8\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 12\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 398\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.17884284812\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00018384356309\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: liblinear_svc_preprocessor\n",
      "  preprocessor:liblinear_svc_preprocessor:C, Value: 20755.6098304\n",
      "  preprocessor:liblinear_svc_preprocessor:dual, Constant: False\n",
      "  preprocessor:liblinear_svc_preprocessor:fit_intercept, Constant: True\n",
      "  preprocessor:liblinear_svc_preprocessor:intercept_scaling, Constant: 1\n",
      "  preprocessor:liblinear_svc_preprocessor:loss, Value: squared_hinge\n",
      "  preprocessor:liblinear_svc_preprocessor:multi_class, Constant: ovr\n",
      "  preprocessor:liblinear_svc_preprocessor:penalty, Constant: l1\n",
      "  preprocessor:liblinear_svc_preprocessor:tol, Value: 0.00202042994347\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:19,179:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 164. configuration. Duration: 0.976017; loss: 0.684426; status 1; additional run info: ;duration: 0.9760172367095947;num_run:00164 \n",
      "[INFO] [2016-08-16 07:56:20,147:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 138 training points for SMAC.\n",
      "[INFO] [2016-08-16 07:56:22,912:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.381148 7: 0.377049 8: 0.377049 9: 0.381148 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.377049 14: 0.377049 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.385246 19: 0.381148 20: 0.377049 21: 0.377049 22: 0.377049 23: 0.377049 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.385246 28: 0.385246 29: 0.385246 30: 0.385246 31: 0.385246 32: 0.385246 33: 0.381148 34: 0.385246 35: 0.385246 36: 0.385246 37: 0.385246 38: 0.381148 39: 0.381148 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.377049 47: 0.377049 48: 0.381148 49: 0.381148\n",
      "\tMembers: [21, 7, 14, 2, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 6, 2, 3, 6, 2, 6, 7, 7, 3, 2, 1, 14, 7, 7, 7, 7, 7, 20, 47, 7, 7, 7, 6, 7, 7, 7, 7, 7, 7, 7, 3, 2, 6, 7]\n",
      "\tWeights: [ 0.    0.02  0.1   0.06  0.    0.    0.1   0.62  0.    0.    0.    0.    0.\n",
      "  0.    0.04  0.    0.    0.    0.    0.    0.02  0.02  0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.  ]\n",
      "\tIdentifiers: (1, 19) (1, 21) (1, 31) (1, 39) (1, 40) (1, 63) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:56:22,938:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:56:22,949:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 6.624661 seconds\n",
      "[INFO] [2016-08-16 07:56:22,954:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run16\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:56:24,988:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:56:25,142:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:56:29,942:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.381148 7: 0.377049 8: 0.377049 9: 0.381148 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.377049 14: 0.377049 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.385246 19: 0.381148 20: 0.377049 21: 0.377049 22: 0.377049 23: 0.377049 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.385246 28: 0.385246 29: 0.385246 30: 0.385246 31: 0.385246 32: 0.385246 33: 0.381148 34: 0.385246 35: 0.385246 36: 0.385246 37: 0.385246 38: 0.381148 39: 0.381148 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.377049 47: 0.377049 48: 0.381148 49: 0.381148\n",
      "\tMembers: [20, 7, 13, 2, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 6, 2, 3, 6, 2, 6, 7, 7, 3, 2, 1, 13, 7, 7, 7, 7, 7, 19, 46, 7, 7, 7, 6, 7, 7, 7, 7, 7, 7, 7, 3, 2, 6, 7]\n",
      "\tWeights: [ 0.    0.02  0.1   0.06  0.    0.    0.1   0.62  0.    0.    0.    0.    0.\n",
      "  0.04  0.    0.    0.    0.    0.    0.02  0.02  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 19) (1, 21) (1, 31) (1, 39) (1, 40) (1, 63) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:56:29,955:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:56:29,958:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 4.982001 seconds\n",
      "[INFO] [2016-08-16 07:56:29,961:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:56:46,440:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 26.2874 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:56:46,446:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 165. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:46,448:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.464449375343\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:47,111:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 165. configuration. Duration: 0.609321; loss: 0.647541; status 1; additional run info: ;duration: 0.609320878982544;num_run:00165 \n",
      "[INFO] [2016-08-16 07:56:47,119:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 166. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:47,121:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.082436911571\n",
      "  classifier:adaboost:max_depth, Value: 9\n",
      "  classifier:adaboost:n_estimators, Value: 283\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: cosine\n",
      "  preprocessor:feature_agglomeration:linkage, Value: average\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 36\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: median\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run16\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:56:48,063:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:56:48,130:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:56:48,972:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 166. configuration. Duration: 1.789099; loss: 0.807377; status 1; additional run info: ;duration: 1.7890987396240234;num_run:00166 \n",
      "[INFO] [2016-08-16 07:56:48,979:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 167. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:48,981:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:49,624:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 167. configuration. Duration: 0.591942; loss: 0.647541; status 1; additional run info: ;duration: 0.591942310333252;num_run:00167 \n",
      "[INFO] [2016-08-16 07:56:49,632:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 168. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:49,634:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: entropy\n",
      "  classifier:decision_tree:max_depth, Value: 1.83605783289\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 1\n",
      "  classifier:decision_tree:min_samples_split, Value: 7\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.266109882375\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 12.2959125875\n",
      "  preprocessor:select_percentile_classification:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:49,688:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 168. configuration. Duration: 0.019612; loss: 0.852459; status 1; additional run info: ;duration: 0.01961231231689453;num_run:00168 \n",
      "[INFO] [2016-08-16 07:56:49,695:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 169. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:49,697:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:50,234:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.381148 7: 0.377049 8: 0.377049 9: 0.381148 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.377049 14: 0.377049 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.385246 19: 0.381148 20: 0.377049 21: 0.377049 22: 0.377049 23: 0.377049 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.372951 28: 0.385246 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.385246 44: 0.385246 45: 0.385246 46: 0.377049 47: 0.381148 48: 0.377049 49: 0.377049\n",
      "\tMembers: [19, 6, 12, 1, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 1, 2, 5, 1, 5, 6, 6, 2, 1, 4, 1, 38, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 45, 6, 6, 3, 19, 6, 6]\n",
      "\tWeights: [ 0.    0.1   0.04  0.02  0.02  0.06  0.66  0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.04  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 21) (1, 31) (1, 34) (1, 37) (1, 39) (1, 40) (1, 63) (1, 79) (1, 123) (1, 149)\n",
      "[INFO] [2016-08-16 07:56:50,242:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.377049\n",
      "[INFO] [2016-08-16 07:56:50,243:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.184792 seconds\n",
      "[INFO] [2016-08-16 07:56:50,247:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (160)!.\n",
      "[INFO] [2016-08-16 07:56:50,249:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (160)!\n",
      "[ERROR] [2016-08-16 07:56:50,260:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:56:50,331:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:56:50,357:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 169. configuration. Duration: 0.606712; loss: 0.647541; status 1; additional run info: ;duration: 0.6067123413085938;num_run:00169 \n",
      "[INFO] [2016-08-16 07:56:50,365:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 170. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:50,367:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 64.4613115513\n",
      "  classifier:bernoulli_nb:fit_prior, Value: False\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 1.50706389678\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 11\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 16\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:50,646:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 170. configuration. Duration: 0.233033; loss: 0.889344; status 1; additional run info: ;duration: 0.2330327033996582;num_run:00170 \n",
      "[INFO] [2016-08-16 07:56:50,654:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 171. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:50,657:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:51,375:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 171. configuration. Duration: 0.655082; loss: 0.647541; status 1; additional run info: ;duration: 0.6550819873809814;num_run:00171 \n",
      "[INFO] [2016-08-16 07:56:51,382:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 172. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:51,384:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 0.0294373722547\n",
      "  classifier:bernoulli_nb:fit_prior, Value: True\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: liblinear_svc_preprocessor\n",
      "  preprocessor:liblinear_svc_preprocessor:C, Value: 10164.1133467\n",
      "  preprocessor:liblinear_svc_preprocessor:dual, Constant: False\n",
      "  preprocessor:liblinear_svc_preprocessor:fit_intercept, Constant: True\n",
      "  preprocessor:liblinear_svc_preprocessor:intercept_scaling, Constant: 1\n",
      "  preprocessor:liblinear_svc_preprocessor:loss, Value: squared_hinge\n",
      "  preprocessor:liblinear_svc_preprocessor:multi_class, Constant: ovr\n",
      "  preprocessor:liblinear_svc_preprocessor:penalty, Constant: l1\n",
      "  preprocessor:liblinear_svc_preprocessor:tol, Value: 0.00247143999705\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:51,457:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 172. configuration. Duration: 0.032361; loss: 0.811475; status 1; additional run info: ;duration: 0.03236103057861328;num_run:00172 \n",
      "[INFO] [2016-08-16 07:56:51,464:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 173. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:51,466:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:52,215:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 173. configuration. Duration: 0.689291; loss: 0.647541; status 1; additional run info: ;duration: 0.6892907619476318;num_run:00173 \n",
      "[INFO] [2016-08-16 07:56:52,223:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 174. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:52,225:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 1.41662177149\n",
      "  classifier:bernoulli_nb:fit_prior, Value: False\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00275401501274\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:56:52,284:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 174. configuration. Duration: 0.018614; loss: 0.872951; status 1; additional run info: ;duration: 0.01861429214477539;num_run:00174 \n",
      "[INFO] [2016-08-16 07:56:52,292:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 175. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:52,295:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:52,708:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.368852 3: 0.377049 4: 0.381148 5: 0.385246 6: 0.381148 7: 0.377049 8: 0.377049 9: 0.381148 10: 0.381148 11: 0.381148 12: 0.381148 13: 0.377049 14: 0.377049 15: 0.372951 16: 0.372951 17: 0.372951 18: 0.385246 19: 0.381148 20: 0.377049 21: 0.377049 22: 0.377049 23: 0.377049 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.372951 28: 0.385246 29: 0.381148 30: 0.381148 31: 0.381148 32: 0.381148 33: 0.381148 34: 0.381148 35: 0.381148 36: 0.381148 37: 0.381148 38: 0.381148 39: 0.381148 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.385246 44: 0.385246 45: 0.385246 46: 0.377049 47: 0.377049 48: 0.377049 49: 0.377049\n",
      "\tMembers: [18, 5, 11, 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 1, 2, 4, 1, 4, 5, 5, 2, 1, 3, 1, 37, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 44, 5, 5, 5, 5, 5, 5]\n",
      "\tWeights: [ 0.    0.1   0.04  0.02  0.06  0.7   0.    0.    0.    0.    0.    0.02\n",
      "  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 21) (1, 31) (1, 37) (1, 39) (1, 40) (1, 63) (1, 79) (1, 123) (1, 149)\n",
      "[INFO] [2016-08-16 07:56:52,716:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.377049\n",
      "[INFO] [2016-08-16 07:56:52,719:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.463970 seconds\n",
      "[INFO] [2016-08-16 07:56:52,723:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (163)!.\n",
      "[INFO] [2016-08-16 07:56:52,726:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (163)!\n",
      "[ERROR] [2016-08-16 07:56:52,739:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:56:52,814:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:56:53,014:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 175. configuration. Duration: 0.659380; loss: 0.647541; status 1; additional run info: ;duration: 0.6593797206878662;num_run:00175 \n",
      "[INFO] [2016-08-16 07:56:53,025:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 176. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:53,028:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 0.0113865755932\n",
      "  classifier:sgd:average, Value: True\n",
      "  classifier:sgd:eta0, Value: 0.059741833941\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: constant\n",
      "  classifier:sgd:loss, Value: perceptron\n",
      "  classifier:sgd:n_iter, Value: 195\n",
      "  classifier:sgd:penalty, Value: l1\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.498479508115\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: deflation\n",
      "  preprocessor:fast_ica:fun, Value: cube\n",
      "  preprocessor:fast_ica:n_components, Value: 620\n",
      "  preprocessor:fast_ica:whiten, Value: True\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "n_components is too large: it will be set to 9\n",
      "[INFO] [2016-08-16 07:56:53,461:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 176. configuration. Duration: 0.393487; loss: 1.159836; status 1; additional run info: ;duration: 0.39348673820495605;num_run:00176 \n",
      "[INFO] [2016-08-16 07:56:53,468:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 177. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:53,470:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0138289887612\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:54,214:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 177. configuration. Duration: 0.686153; loss: 0.647541; status 1; additional run info: ;duration: 0.6861526966094971;num_run:00177 \n",
      "[INFO] [2016-08-16 07:56:54,224:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 178. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:54,227:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.227552709207\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 10\n",
      "  classifier:gradient_boosting:max_features, Value: 3.33583602153\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 11\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 136\n",
      "  classifier:gradient_boosting:subsample, Value: 0.221801564857\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000120541543842\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: exp\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 116, in _ica_par\n",
      "    warnings.warn('FastICA did not converge. Consider increasing '\n",
      "UserWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:55,285:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.368852 9: 0.372951 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.368852 14: 0.368852 15: 0.377049 16: 0.377049 17: 0.377049 18: 0.377049 19: 0.377049 20: 0.377049 21: 0.377049 22: 0.377049 23: 0.377049 24: 0.381148 25: 0.381148 26: 0.381148 27: 0.377049 28: 0.377049 29: 0.377049 30: 0.377049 31: 0.377049 32: 0.381148 33: 0.385246 34: 0.385246 35: 0.381148 36: 0.381148 37: 0.377049 38: 0.381148 39: 0.381148 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.393443 45: 0.393443 46: 0.393443 47: 0.389344 48: 0.389344 49: 0.389344\n",
      "\tMembers: [16, 5, 5, 16, 5, 16, 41, 10, 15, 0, 13, 5, 5, 1, 2, 36, 1, 5, 5, 5, 5, 5, 5, 5, 41, 5, 5, 5, 5, 5, 5, 3, 15, 5, 5, 5, 5, 2, 15, 5, 5, 5, 13, 1, 2, 5, 5, 5, 5, 5]\n",
      "\tWeights: [ 0.02  0.06  0.06  0.02  0.    0.6   0.    0.    0.    0.    0.02  0.    0.\n",
      "  0.04  0.    0.06  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.\n",
      "  0.    0.    0.04  0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 13) (1, 21) (1, 31) (1, 37) (1, 40) (1, 65) (1, 69) (1, 73) (1, 79) (1, 126) (1, 149)\n",
      "[INFO] [2016-08-16 07:56:55,292:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.389344\n",
      "[INFO] [2016-08-16 07:56:55,294:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.560404 seconds\n",
      "[INFO] [2016-08-16 07:56:55,297:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (169)!.\n",
      "[INFO] [2016-08-16 07:56:55,299:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (169)!\n",
      "[ERROR] [2016-08-16 07:56:55,311:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:56:55,384:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:56:55,458:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 178. configuration. Duration: 1.222356; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:56:55,467:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 179. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:55,469:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[ERROR] [2016-08-16 07:56:55,496:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:56:56,195:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 179. configuration. Duration: 0.669811; loss: 0.647541; status 1; additional run info: ;duration: 0.6698112487792969;num_run:00179 \n",
      "[INFO] [2016-08-16 07:56:56,204:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 180. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:56,207:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: gini\n",
      "  classifier:decision_tree:max_depth, Value: 0.228822287652\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 17\n",
      "  classifier:decision_tree:min_samples_split, Value: 2\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00208599333996\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: deflation\n",
      "  preprocessor:fast_ica:fun, Value: cube\n",
      "  preprocessor:fast_ica:n_components, Value: 1219\n",
      "  preprocessor:fast_ica:whiten, Value: True\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "n_components is too large: it will be set to 9\n",
      "[INFO] [2016-08-16 07:56:56,336:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 180. configuration. Duration: 0.090675; loss: 0.770492; status 1; additional run info: ;duration: 0.09067535400390625;num_run:00180 \n",
      "[INFO] [2016-08-16 07:56:56,345:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 181. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:56,347:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.0404096759333\n",
      "  classifier:adaboost:max_depth, Value: 1\n",
      "  classifier:adaboost:n_estimators, Value: 465\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:56:57,223:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 181. configuration. Duration: 0.799992; loss: 0.803279; status 1; additional run info: ;duration: 0.7999916076660156;num_run:00181 \n",
      "[INFO] [2016-08-16 07:56:57,232:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 182. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:57,235:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 129\n",
      "  classifier:lda:shrinkage, Value: None\n",
      "  classifier:lda:tol, Value: 0.0858733688445\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:56:57,303:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 182. configuration. Duration: 0.026963; loss: 0.725410; status 1; additional run info: ;duration: 0.0269625186920166;num_run:00182 \n",
      "[INFO] [2016-08-16 07:56:57,313:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 183. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:57,316:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 2.44638253826\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 11\n",
      "  classifier:random_forest:min_samples_split, Value: 18\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00683265751935\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:56:57,618:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 183. configuration. Duration: 0.253443; loss: 0.680328; status 1; additional run info: ;duration: 0.25344324111938477;num_run:00183 \n",
      "[INFO] [2016-08-16 07:56:57,626:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 184. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:57,628:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gaussian_nb\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0111264470674\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: True\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 2.6722951724\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 11\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 9\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:57,802:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.368852 9: 0.372951 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.368852 14: 0.364754 15: 0.377049 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.368852 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.377049 29: 0.377049 30: 0.377049 31: 0.377049 32: 0.377049 33: 0.377049 34: 0.377049 35: 0.372951 36: 0.377049 37: 0.377049 38: 0.377049 39: 0.377049 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [15, 4, 4, 15, 4, 15, 39, 9, 14, 0, 12, 4, 4, 1, 3, 10, 4, 2, 4, 4, 4, 4, 1, 0, 10, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 1, 3, 2, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4]\n",
      "\tWeights: [ 0.04  0.06  0.06  0.08  0.58  0.    0.    0.    0.    0.02  0.04  0.\n",
      "  0.02  0.    0.02  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 13) (1, 21) (1, 37) (1, 39) (1, 40) (1, 65) (1, 67) (1, 69) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:56:57,811:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:56:57,813:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.507314 seconds\n",
      "[INFO] [2016-08-16 07:56:57,816:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (172)!.\n",
      "[INFO] [2016-08-16 07:56:57,818:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (172)!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:56:57,830:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:56:57,905:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 184. configuration. Duration: 0.229496; loss: 0.713115; status 1; additional run info: ;duration: 0.22949624061584473;num_run:00184 \n",
      "[ERROR] [2016-08-16 07:56:57,907:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:56:57,915:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 185. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:57,917:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.285378581226\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 8\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 12\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 229\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.635219713353\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000544544963901\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[ERROR] [2016-08-16 07:56:58,024:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:56:58,595:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 185. configuration. Duration: 0.638471; loss: 0.733607; status 1; additional run info: ;duration: 0.6384713649749756;num_run:00185 \n",
      "[INFO] [2016-08-16 07:56:58,603:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 186. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:58,605:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gaussian_nb\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.190921236574\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: exp\n",
      "  preprocessor:fast_ica:n_components, Value: 844\n",
      "  preprocessor:fast_ica:whiten, Value: True\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "n_components is too large: it will be set to 9\n",
      "[INFO] [2016-08-16 07:56:58,732:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 186. configuration. Duration: 0.048867; loss: 0.745902; status 1; additional run info: ;duration: 0.04886674880981445;num_run:00186 \n",
      "[INFO] [2016-08-16 07:56:58,741:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 187. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:58,743:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.072494349798\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 8\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 7\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 81\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.0872885268293\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 13\n",
      "  preprocessor:gem:precond, Value: 0.247644101237\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:56:59,082:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 187. configuration. Duration: 0.299846; loss: 0.713115; status 1; additional run info: ;duration: 0.29984617233276367;num_run:00187 \n",
      "[INFO] [2016-08-16 07:56:59,090:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 188. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:56:59,092:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gaussian_nb\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:coef0, Value: 0.631472001441\n",
      "  preprocessor:kernel_pca:kernel, Value: sigmoid\n",
      "  preprocessor:kernel_pca:n_components, Value: 279\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 148, in _pre_transform\n",
      "    .transform(Xt)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/kernel_pca.py\", line 53, in transform\n",
      "    raise ValueError(\"KernelPCA removed all features!\")\n",
      "ValueError: KernelPCA removed all features!\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:57:00,361:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 188. configuration. Duration: 1.260324; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:57:00,370:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 189. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:00,372:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.433927756858\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 8\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 11\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 310\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.144428241987\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:00,718:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 189. configuration. Duration: 0.300743; loss: 0.704918; status 1; additional run info: ;duration: 0.30074334144592285;num_run:00189 \n",
      "[INFO] [2016-08-16 07:57:00,728:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 190. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:00,730:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: qda\n",
      "  classifier:qda:reg_param, Value: 5.55703591689\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000277356064305\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:kernel, Value: cosine\n",
      "  preprocessor:kernel_pca:n_components, Value: 163\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:00,808:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.368852 9: 0.372951 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.368852 14: 0.364754 15: 0.377049 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.368852 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.377049 29: 0.377049 30: 0.377049 31: 0.377049 32: 0.377049 33: 0.377049 34: 0.377049 35: 0.372951 36: 0.377049 37: 0.377049 38: 0.377049 39: 0.377049 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [13, 4, 4, 13, 4, 13, 37, 7, 12, 0, 10, 4, 4, 1, 3, 8, 4, 2, 4, 4, 4, 4, 1, 0, 8, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 1, 3, 2, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4]\n",
      "\tWeights: [ 0.04  0.06  0.06  0.08  0.58  0.    0.    0.02  0.04  0.    0.02  0.\n",
      "  0.02  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 13) (1, 21) (1, 37) (1, 39) (1, 40) (1, 65) (1, 67) (1, 69) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:00,816:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:57:00,818:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.994050 seconds\n",
      "[INFO] [2016-08-16 07:57:00,838:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/discriminant_analysis.py:688: UserWarning: Variables are collinear\n",
      "  warnings.warn(\"Variables are collinear\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:57:01,214:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 190. configuration. Duration: 0.406752; loss: 0.877049; status 1; additional run info: ;duration: 0.4067518711090088;num_run:00190 \n",
      "[INFO] [2016-08-16 07:57:01,223:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 191. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:01,225:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.0228337656859\n",
      "  classifier:adaboost:max_depth, Value: 6\n",
      "  classifier:adaboost:n_estimators, Value: 218\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00053752512301\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 18\n",
      "  preprocessor:gem:precond, Value: 0.345685570452\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:57:02,858:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:57:02,959:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:57:03,131:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:57:04,999:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 191. configuration. Duration: 3.706326; loss: 0.856557; status 1; additional run info: ;duration: 3.7063255310058594;num_run:00191 \n",
      "[INFO] [2016-08-16 07:57:05,009:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 192. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:05,015:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 0.75563116613\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 9\n",
      "  classifier:extra_trees:min_samples_split, Value: 13\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.492722090532\n",
      "  preprocessor:select_rates:mode, Value: fdr\n",
      "  preprocessor:select_rates:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:57:05,327:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 192. configuration. Duration: 0.255367; loss: 0.725410; status 1; additional run info: ;duration: 0.25536656379699707;num_run:00192 \n",
      "[INFO] [2016-08-16 07:57:05,338:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 193. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:05,342:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 1.22709021285\n",
      "  classifier:adaboost:max_depth, Value: 8\n",
      "  classifier:adaboost:n_estimators, Value: 234\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0446458489034\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 93.9542819586\n",
      "  preprocessor:select_percentile_classification:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:05,796:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.368852 9: 0.372951 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.368852 14: 0.364754 15: 0.377049 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.368852 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.377049 29: 0.377049 30: 0.377049 31: 0.377049 32: 0.377049 33: 0.377049 34: 0.377049 35: 0.372951 36: 0.377049 37: 0.377049 38: 0.377049 39: 0.377049 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [13, 4, 4, 13, 4, 13, 37, 7, 12, 0, 10, 4, 4, 1, 3, 8, 4, 2, 4, 4, 4, 4, 1, 0, 8, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 1, 3, 2, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4]\n",
      "\tWeights: [ 0.04  0.06  0.06  0.08  0.58  0.    0.    0.02  0.04  0.    0.02  0.\n",
      "  0.02  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 13) (1, 21) (1, 37) (1, 39) (1, 40) (1, 65) (1, 67) (1, 69) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:05,804:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:57:05,807:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.955733 seconds\n",
      "[INFO] [2016-08-16 07:57:05,809:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:57:06,262:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 193. configuration. Duration: 0.847360; loss: 0.770492; status 1; additional run info: ;duration: 0.8473598957061768;num_run:00193 \n",
      "[INFO] [2016-08-16 07:57:06,272:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 194. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:06,273:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME.R\n",
      "  classifier:adaboost:learning_rate, Value: 0.411057351669\n",
      "  classifier:adaboost:max_depth, Value: 7\n",
      "  classifier:adaboost:n_estimators, Value: 462\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: manhattan\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 394\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: max\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:57:07,836:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:57:07,911:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:57:07,927:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 194. configuration. Duration: 1.566479; loss: 0.774590; status 1; additional run info: ;duration: 1.5664787292480469;num_run:00194 \n",
      "[INFO] [2016-08-16 07:57:07,936:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 195. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:07,938:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 1.41778154608\n",
      "  classifier:adaboost:max_depth, Value: 8\n",
      "  classifier:adaboost:n_estimators, Value: 351\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00305515385341\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: True\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 2.57932465698\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 2\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 5\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[ERROR] [2016-08-16 07:57:08,032:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:57:09,196:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 195. configuration. Duration: 1.166501; loss: 0.729508; status 1; additional run info: ;duration: 1.1665012836456299;num_run:00195 \n",
      "[INFO] [2016-08-16 07:57:09,204:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 196. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:09,206:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: k_nearest_neighbors\n",
      "  classifier:k_nearest_neighbors:n_neighbors, Value: 5\n",
      "  classifier:k_nearest_neighbors:p, Value: 1\n",
      "  classifier:k_nearest_neighbors:weights, Value: distance\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0210628354718\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: liblinear_svc_preprocessor\n",
      "  preprocessor:liblinear_svc_preprocessor:C, Value: 139.430670113\n",
      "  preprocessor:liblinear_svc_preprocessor:dual, Constant: False\n",
      "  preprocessor:liblinear_svc_preprocessor:fit_intercept, Constant: True\n",
      "  preprocessor:liblinear_svc_preprocessor:intercept_scaling, Constant: 1\n",
      "  preprocessor:liblinear_svc_preprocessor:loss, Value: squared_hinge\n",
      "  preprocessor:liblinear_svc_preprocessor:multi_class, Constant: ovr\n",
      "  preprocessor:liblinear_svc_preprocessor:penalty, Constant: l1\n",
      "  preprocessor:liblinear_svc_preprocessor:tol, Value: 0.00708203034599\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:57:09,281:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 196. configuration. Duration: 0.037103; loss: 0.848361; status 1; additional run info: ;duration: 0.03710341453552246;num_run:00196 \n",
      "[INFO] [2016-08-16 07:57:09,289:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 197. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:09,291:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: k_nearest_neighbors\n",
      "  classifier:k_nearest_neighbors:n_neighbors, Value: 1\n",
      "  classifier:k_nearest_neighbors:p, Value: 2\n",
      "  classifier:k_nearest_neighbors:weights, Value: distance\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: gem\n",
      "  preprocessor:gem:N, Value: 19\n",
      "  preprocessor:gem:precond, Value: 0.111302568621\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:57:09,420:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 197. configuration. Duration: 0.080479; loss: 0.823770; status 1; additional run info: ;duration: 0.08047914505004883;num_run:00197 \n",
      "[INFO] [2016-08-16 07:57:09,429:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 198. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:09,432:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.377724405606\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 8\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 5\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 271\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.637377828804\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 9\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 3\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 16\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 70\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:10,345:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.368852 9: 0.372951 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.368852 14: 0.364754 15: 0.377049 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.368852 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.377049 29: 0.377049 30: 0.377049 31: 0.377049 32: 0.377049 33: 0.377049 34: 0.377049 35: 0.372951 36: 0.377049 37: 0.377049 38: 0.377049 39: 0.377049 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [13, 4, 4, 13, 4, 13, 37, 7, 12, 0, 10, 4, 4, 1, 3, 8, 4, 2, 4, 4, 4, 4, 1, 0, 8, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 1, 3, 2, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4]\n",
      "\tWeights: [ 0.04  0.06  0.06  0.08  0.58  0.    0.    0.02  0.04  0.    0.02  0.\n",
      "  0.02  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 13) (1, 21) (1, 37) (1, 39) (1, 40) (1, 65) (1, 67) (1, 69) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:10,354:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:57:10,357:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.526227 seconds\n",
      "[INFO] [2016-08-16 07:57:10,359:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:57:12,378:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:57:12,448:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:57:12,556:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 60, in fit_predict_and_loss\n",
      "    return self.predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 115, in predict_and_loss\n",
      "    Y_optimization_pred, Y_valid_pred, Y_test_pred = self._predict()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 98, in _predict\n",
      "    self.Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/abstract_evaluator.py\", line 266, in _predict_proba\n",
      "    Y_pred = model.predict_proba(X, batch_size=1000)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 120, in predict_proba\n",
      "    target = self.predict_proba(X[0:2].copy())\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 112, in predict_proba\n",
      "    return self.pipeline_.steps[-1][-1].predict_proba(Xt)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/classification/xgradient_boosting.py\", line 141, in predict_proba\n",
      "    return self.estimator.predict_proba(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/xgboost/sklearn.py\", line 477, in predict_proba\n",
      "    ntree_limit=ntree_limit)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/xgboost/core.py\", line 939, in predict\n",
      "    self._validate_features(data)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/xgboost/core.py\", line 1179, in _validate_features\n",
      "    data.feature_names))\n",
      "ValueError: feature_names mismatch: ['f0', 'f1', 'f2', 'f3', 'f4', 'f5', 'f6', 'f7', 'f8', 'f9', 'f10', 'f11', 'f12', 'f13', 'f14', 'f15', 'f16', 'f17', 'f18', 'f19', 'f20', 'f21', 'f22', 'f23', 'f24', 'f25', 'f26', 'f27', 'f28', 'f29', 'f30', 'f31', 'f32', 'f33', 'f34', 'f35', 'f36', 'f37', 'f38', 'f39', 'f40', 'f41', 'f42', 'f43', 'f44', 'f45', 'f46', 'f47', 'f48', 'f49', 'f50', 'f51', 'f52', 'f53', 'f54', 'f55', 'f56', 'f57', 'f58', 'f59', 'f60', 'f61', 'f62', 'f63', 'f64', 'f65', 'f66', 'f67', 'f68', 'f69', 'f70', 'f71', 'f72', 'f73', 'f74', 'f75', 'f76', 'f77', 'f78', 'f79', 'f80', 'f81', 'f82', 'f83', 'f84', 'f85', 'f86', 'f87', 'f88', 'f89', 'f90', 'f91', 'f92', 'f93', 'f94', 'f95', 'f96', 'f97', 'f98', 'f99', 'f100', 'f101', 'f102', 'f103', 'f104', 'f105', 'f106', 'f107', 'f108', 'f109', 'f110', 'f111', 'f112', 'f113', 'f114', 'f115', 'f116', 'f117', 'f118', 'f119', 'f120', 'f121', 'f122', 'f123', 'f124', 'f125', 'f126', 'f127', 'f128', 'f129', 'f130', 'f131', 'f132', 'f133', 'f134', 'f135', 'f136', 'f137', 'f138', 'f139', 'f140', 'f141', 'f142', 'f143', 'f144', 'f145', 'f146', 'f147', 'f148', 'f149', 'f150', 'f151', 'f152', 'f153', 'f154', 'f155', 'f156', 'f157', 'f158', 'f159', 'f160', 'f161', 'f162', 'f163', 'f164', 'f165', 'f166', 'f167', 'f168', 'f169', 'f170', 'f171', 'f172', 'f173', 'f174', 'f175', 'f176', 'f177', 'f178', 'f179', 'f180', 'f181', 'f182', 'f183', 'f184', 'f185', 'f186', 'f187', 'f188', 'f189', 'f190', 'f191', 'f192', 'f193', 'f194', 'f195', 'f196', 'f197', 'f198', 'f199', 'f200', 'f201', 'f202', 'f203', 'f204', 'f205', 'f206', 'f207', 'f208', 'f209', 'f210', 'f211', 'f212', 'f213', 'f214', 'f215', 'f216', 'f217', 'f218', 'f219', 'f220', 'f221', 'f222', 'f223', 'f224', 'f225', 'f226', 'f227', 'f228', 'f229', 'f230', 'f231', 'f232', 'f233', 'f234', 'f235', 'f236', 'f237', 'f238', 'f239', 'f240', 'f241', 'f242', 'f243', 'f244', 'f245', 'f246', 'f247', 'f248', 'f249', 'f250', 'f251', 'f252', 'f253', 'f254', 'f255', 'f256', 'f257', 'f258', 'f259', 'f260', 'f261', 'f262', 'f263', 'f264', 'f265', 'f266', 'f267', 'f268', 'f269', 'f270', 'f271', 'f272', 'f273', 'f274', 'f275', 'f276', 'f277', 'f278', 'f279', 'f280', 'f281', 'f282', 'f283', 'f284', 'f285', 'f286', 'f287', 'f288', 'f289', 'f290', 'f291', 'f292', 'f293', 'f294', 'f295', 'f296', 'f297', 'f298', 'f299', 'f300', 'f301', 'f302', 'f303', 'f304', 'f305', 'f306', 'f307', 'f308', 'f309', 'f310', 'f311', 'f312', 'f313', 'f314', 'f315', 'f316', 'f317', 'f318', 'f319', 'f320', 'f321', 'f322', 'f323', 'f324', 'f325', 'f326', 'f327', 'f328', 'f329', 'f330', 'f331', 'f332', 'f333', 'f334', 'f335', 'f336', 'f337', 'f338', 'f339', 'f340', 'f341', 'f342', 'f343', 'f344', 'f345', 'f346', 'f347', 'f348', 'f349', 'f350', 'f351', 'f352', 'f353', 'f354', 'f355', 'f356', 'f357', 'f358', 'f359', 'f360', 'f361', 'f362', 'f363', 'f364', 'f365', 'f366', 'f367', 'f368', 'f369', 'f370', 'f371', 'f372', 'f373', 'f374', 'f375', 'f376', 'f377', 'f378', 'f379', 'f380', 'f381', 'f382', 'f383', 'f384', 'f385', 'f386', 'f387', 'f388', 'f389', 'f390', 'f391', 'f392', 'f393', 'f394', 'f395', 'f396', 'f397', 'f398', 'f399', 'f400', 'f401', 'f402', 'f403', 'f404', 'f405', 'f406', 'f407', 'f408', 'f409', 'f410', 'f411', 'f412', 'f413', 'f414', 'f415', 'f416', 'f417', 'f418', 'f419', 'f420', 'f421', 'f422', 'f423', 'f424', 'f425', 'f426', 'f427', 'f428', 'f429', 'f430', 'f431', 'f432', 'f433', 'f434', 'f435', 'f436', 'f437', 'f438', 'f439', 'f440', 'f441', 'f442', 'f443', 'f444', 'f445', 'f446', 'f447', 'f448', 'f449', 'f450', 'f451', 'f452', 'f453', 'f454', 'f455', 'f456', 'f457', 'f458', 'f459', 'f460', 'f461', 'f462', 'f463', 'f464', 'f465', 'f466', 'f467', 'f468', 'f469', 'f470', 'f471', 'f472', 'f473', 'f474', 'f475', 'f476', 'f477', 'f478', 'f479', 'f480', 'f481', 'f482', 'f483', 'f484', 'f485', 'f486', 'f487', 'f488', 'f489', 'f490', 'f491', 'f492', 'f493', 'f494', 'f495', 'f496', 'f497', 'f498', 'f499', 'f500', 'f501', 'f502', 'f503', 'f504', 'f505', 'f506', 'f507', 'f508', 'f509', 'f510', 'f511', 'f512', 'f513', 'f514', 'f515', 'f516', 'f517', 'f518', 'f519', 'f520', 'f521', 'f522', 'f523', 'f524', 'f525', 'f526', 'f527', 'f528', 'f529', 'f530', 'f531', 'f532', 'f533', 'f534', 'f535', 'f536', 'f537', 'f538', 'f539', 'f540', 'f541', 'f542', 'f543', 'f544', 'f545', 'f546', 'f547', 'f548', 'f549', 'f550', 'f551', 'f552', 'f553', 'f554', 'f555', 'f556', 'f557', 'f558', 'f559', 'f560', 'f561', 'f562', 'f563', 'f564', 'f565', 'f566', 'f567', 'f568', 'f569', 'f570', 'f571', 'f572', 'f573', 'f574', 'f575', 'f576', 'f577', 'f578', 'f579', 'f580', 'f581', 'f582', 'f583', 'f584', 'f585', 'f586', 'f587', 'f588', 'f589', 'f590', 'f591', 'f592', 'f593', 'f594', 'f595', 'f596', 'f597', 'f598', 'f599', 'f600', 'f601', 'f602', 'f603', 'f604', 'f605', 'f606', 'f607', 'f608', 'f609', 'f610', 'f611', 'f612', 'f613', 'f614', 'f615', 'f616', 'f617', 'f618', 'f619', 'f620', 'f621', 'f622', 'f623', 'f624', 'f625', 'f626', 'f627', 'f628', 'f629', 'f630', 'f631', 'f632', 'f633', 'f634', 'f635', 'f636', 'f637', 'f638', 'f639', 'f640', 'f641', 'f642', 'f643', 'f644', 'f645', 'f646', 'f647', 'f648', 'f649', 'f650', 'f651', 'f652', 'f653', 'f654', 'f655', 'f656', 'f657', 'f658', 'f659', 'f660', 'f661', 'f662', 'f663', 'f664', 'f665', 'f666', 'f667', 'f668', 'f669', 'f670', 'f671', 'f672', 'f673', 'f674', 'f675', 'f676', 'f677', 'f678', 'f679', 'f680', 'f681', 'f682', 'f683', 'f684', 'f685', 'f686', 'f687', 'f688', 'f689', 'f690', 'f691', 'f692', 'f693', 'f694', 'f695', 'f696', 'f697', 'f698', 'f699', 'f700', 'f701', 'f702', 'f703', 'f704', 'f705', 'f706', 'f707', 'f708', 'f709', 'f710', 'f711', 'f712', 'f713', 'f714', 'f715', 'f716', 'f717', 'f718', 'f719', 'f720', 'f721', 'f722', 'f723', 'f724', 'f725', 'f726', 'f727', 'f728', 'f729', 'f730', 'f731', 'f732', 'f733', 'f734', 'f735', 'f736', 'f737', 'f738', 'f739', 'f740', 'f741', 'f742', 'f743', 'f744', 'f745', 'f746', 'f747', 'f748', 'f749', 'f750', 'f751', 'f752', 'f753', 'f754', 'f755', 'f756', 'f757', 'f758', 'f759', 'f760', 'f761', 'f762', 'f763', 'f764', 'f765', 'f766', 'f767', 'f768', 'f769', 'f770', 'f771', 'f772', 'f773', 'f774', 'f775', 'f776', 'f777', 'f778', 'f779', 'f780', 'f781', 'f782', 'f783', 'f784', 'f785', 'f786', 'f787', 'f788', 'f789', 'f790', 'f791', 'f792', 'f793', 'f794', 'f795', 'f796', 'f797', 'f798', 'f799', 'f800', 'f801', 'f802', 'f803', 'f804', 'f805', 'f806', 'f807', 'f808', 'f809', 'f810', 'f811', 'f812', 'f813', 'f814', 'f815', 'f816', 'f817', 'f818', 'f819', 'f820', 'f821', 'f822', 'f823', 'f824', 'f825', 'f826', 'f827', 'f828', 'f829', 'f830', 'f831', 'f832', 'f833', 'f834', 'f835', 'f836', 'f837', 'f838', 'f839', 'f840', 'f841', 'f842', 'f843', 'f844', 'f845', 'f846', 'f847', 'f848', 'f849', 'f850', 'f851', 'f852', 'f853', 'f854', 'f855', 'f856', 'f857', 'f858', 'f859', 'f860', 'f861', 'f862', 'f863', 'f864', 'f865', 'f866', 'f867', 'f868', 'f869', 'f870', 'f871', 'f872', 'f873', 'f874', 'f875', 'f876', 'f877', 'f878', 'f879', 'f880', 'f881', 'f882', 'f883', 'f884', 'f885', 'f886', 'f887', 'f888', 'f889', 'f890', 'f891', 'f892', 'f893', 'f894', 'f895', 'f896', 'f897', 'f898', 'f899', 'f900', 'f901', 'f902', 'f903', 'f904', 'f905', 'f906', 'f907', 'f908', 'f909', 'f910', 'f911', 'f912', 'f913', 'f914', 'f915', 'f916', 'f917', 'f918', 'f919', 'f920', 'f921', 'f922', 'f923', 'f924', 'f925', 'f926', 'f927', 'f928', 'f929', 'f930', 'f931', 'f932', 'f933', 'f934', 'f935', 'f936', 'f937', 'f938', 'f939', 'f940', 'f941', 'f942', 'f943', 'f944', 'f945', 'f946', 'f947', 'f948', 'f949', 'f950', 'f951', 'f952', 'f953', 'f954', 'f955', 'f956', 'f957', 'f958', 'f959', 'f960', 'f961', 'f962', 'f963', 'f964', 'f965', 'f966', 'f967', 'f968', 'f969', 'f970', 'f971', 'f972', 'f973', 'f974', 'f975', 'f976', 'f977', 'f978', 'f979', 'f980', 'f981', 'f982', 'f983', 'f984', 'f985', 'f986', 'f987', 'f988', 'f989', 'f990', 'f991', 'f992', 'f993', 'f994', 'f995', 'f996', 'f997', 'f998', 'f999', 'f1000', 'f1001', 'f1002', 'f1003', 'f1004', 'f1005', 'f1006', 'f1007', 'f1008', 'f1009', 'f1010', 'f1011', 'f1012', 'f1013', 'f1014', 'f1015', 'f1016', 'f1017', 'f1018', 'f1019', 'f1020', 'f1021', 'f1022', 'f1023', 'f1024', 'f1025', 'f1026', 'f1027', 'f1028', 'f1029', 'f1030', 'f1031', 'f1032', 'f1033', 'f1034', 'f1035', 'f1036', 'f1037', 'f1038', 'f1039', 'f1040', 'f1041', 'f1042', 'f1043', 'f1044', 'f1045', 'f1046', 'f1047', 'f1048', 'f1049', 'f1050', 'f1051', 'f1052', 'f1053', 'f1054', 'f1055', 'f1056', 'f1057', 'f1058', 'f1059', 'f1060', 'f1061', 'f1062', 'f1063', 'f1064', 'f1065', 'f1066', 'f1067', 'f1068', 'f1069', 'f1070', 'f1071', 'f1072', 'f1073', 'f1074', 'f1075', 'f1076', 'f1077', 'f1078', 'f1079', 'f1080', 'f1081', 'f1082', 'f1083', 'f1084', 'f1085', 'f1086', 'f1087', 'f1088', 'f1089', 'f1090', 'f1091', 'f1092', 'f1093', 'f1094', 'f1095', 'f1096', 'f1097', 'f1098', 'f1099', 'f1100', 'f1101', 'f1102', 'f1103', 'f1104', 'f1105', 'f1106', 'f1107', 'f1108', 'f1109', 'f1110', 'f1111', 'f1112', 'f1113', 'f1114', 'f1115', 'f1116', 'f1117', 'f1118', 'f1119', 'f1120', 'f1121', 'f1122', 'f1123', 'f1124', 'f1125', 'f1126', 'f1127', 'f1128', 'f1129', 'f1130', 'f1131', 'f1132', 'f1133', 'f1134', 'f1135', 'f1136', 'f1137', 'f1138', 'f1139', 'f1140', 'f1141', 'f1142', 'f1143', 'f1144', 'f1145', 'f1146', 'f1147', 'f1148', 'f1149', 'f1150', 'f1151', 'f1152', 'f1153', 'f1154', 'f1155', 'f1156', 'f1157', 'f1158', 'f1159', 'f1160', 'f1161', 'f1162', 'f1163', 'f1164', 'f1165', 'f1166', 'f1167', 'f1168', 'f1169', 'f1170', 'f1171', 'f1172', 'f1173', 'f1174', 'f1175', 'f1176', 'f1177', 'f1178', 'f1179', 'f1180', 'f1181', 'f1182', 'f1183', 'f1184', 'f1185', 'f1186', 'f1187', 'f1188', 'f1189', 'f1190', 'f1191', 'f1192', 'f1193', 'f1194', 'f1195', 'f1196', 'f1197', 'f1198', 'f1199', 'f1200', 'f1201', 'f1202', 'f1203', 'f1204', 'f1205', 'f1206', 'f1207', 'f1208', 'f1209', 'f1210', 'f1211', 'f1212', 'f1213', 'f1214', 'f1215', 'f1216', 'f1217', 'f1218', 'f1219', 'f1220', 'f1221', 'f1222', 'f1223', 'f1224', 'f1225', 'f1226', 'f1227', 'f1228', 'f1229', 'f1230', 'f1231', 'f1232', 'f1233', 'f1234', 'f1235', 'f1236', 'f1237', 'f1238', 'f1239', 'f1240', 'f1241', 'f1242', 'f1243', 'f1244', 'f1245', 'f1246', 'f1247', 'f1248', 'f1249', 'f1250', 'f1251', 'f1252', 'f1253', 'f1254', 'f1255', 'f1256', 'f1257', 'f1258', 'f1259', 'f1260', 'f1261', 'f1262', 'f1263', 'f1264', 'f1265', 'f1266', 'f1267', 'f1268', 'f1269', 'f1270', 'f1271', 'f1272', 'f1273', 'f1274', 'f1275', 'f1276', 'f1277', 'f1278', 'f1279', 'f1280', 'f1281', 'f1282', 'f1283', 'f1284', 'f1285', 'f1286', 'f1287', 'f1288', 'f1289', 'f1290', 'f1291', 'f1292', 'f1293', 'f1294', 'f1295', 'f1296', 'f1297', 'f1298', 'f1299', 'f1300', 'f1301', 'f1302', 'f1303', 'f1304', 'f1305', 'f1306', 'f1307', 'f1308', 'f1309', 'f1310', 'f1311', 'f1312', 'f1313', 'f1314', 'f1315', 'f1316', 'f1317', 'f1318', 'f1319', 'f1320', 'f1321', 'f1322', 'f1323', 'f1324', 'f1325', 'f1326', 'f1327', 'f1328', 'f1329', 'f1330', 'f1331', 'f1332', 'f1333', 'f1334', 'f1335', 'f1336', 'f1337', 'f1338', 'f1339', 'f1340', 'f1341', 'f1342', 'f1343', 'f1344', 'f1345', 'f1346', 'f1347', 'f1348', 'f1349', 'f1350', 'f1351', 'f1352', 'f1353', 'f1354', 'f1355', 'f1356', 'f1357', 'f1358', 'f1359', 'f1360', 'f1361', 'f1362', 'f1363', 'f1364', 'f1365', 'f1366', 'f1367', 'f1368', 'f1369', 'f1370', 'f1371', 'f1372', 'f1373', 'f1374', 'f1375', 'f1376', 'f1377', 'f1378', 'f1379', 'f1380', 'f1381', 'f1382', 'f1383', 'f1384', 'f1385', 'f1386', 'f1387', 'f1388', 'f1389', 'f1390', 'f1391', 'f1392', 'f1393', 'f1394', 'f1395', 'f1396', 'f1397', 'f1398', 'f1399', 'f1400', 'f1401', 'f1402', 'f1403', 'f1404', 'f1405', 'f1406', 'f1407', 'f1408', 'f1409', 'f1410', 'f1411', 'f1412', 'f1413', 'f1414', 'f1415', 'f1416', 'f1417', 'f1418', 'f1419', 'f1420', 'f1421', 'f1422', 'f1423', 'f1424', 'f1425', 'f1426', 'f1427', 'f1428', 'f1429', 'f1430', 'f1431', 'f1432', 'f1433', 'f1434', 'f1435', 'f1436', 'f1437', 'f1438', 'f1439', 'f1440', 'f1441', 'f1442', 'f1443', 'f1444', 'f1445', 'f1446', 'f1447', 'f1448', 'f1449', 'f1450', 'f1451', 'f1452', 'f1453', 'f1454', 'f1455', 'f1456', 'f1457', 'f1458', 'f1459', 'f1460', 'f1461', 'f1462', 'f1463', 'f1464', 'f1465', 'f1466', 'f1467', 'f1468', 'f1469', 'f1470', 'f1471', 'f1472', 'f1473', 'f1474', 'f1475', 'f1476', 'f1477', 'f1478', 'f1479', 'f1480', 'f1481', 'f1482', 'f1483', 'f1484', 'f1485', 'f1486', 'f1487', 'f1488', 'f1489', 'f1490', 'f1491', 'f1492', 'f1493', 'f1494', 'f1495', 'f1496', 'f1497', 'f1498', 'f1499', 'f1500', 'f1501', 'f1502', 'f1503', 'f1504', 'f1505', 'f1506', 'f1507', 'f1508', 'f1509', 'f1510', 'f1511', 'f1512', 'f1513', 'f1514', 'f1515', 'f1516', 'f1517', 'f1518', 'f1519', 'f1520', 'f1521', 'f1522', 'f1523', 'f1524', 'f1525', 'f1526', 'f1527', 'f1528', 'f1529', 'f1530', 'f1531', 'f1532', 'f1533', 'f1534', 'f1535', 'f1536', 'f1537', 'f1538', 'f1539', 'f1540', 'f1541', 'f1542', 'f1543', 'f1544', 'f1545', 'f1546', 'f1547', 'f1548', 'f1549', 'f1550', 'f1551', 'f1552', 'f1553', 'f1554', 'f1555', 'f1556', 'f1557', 'f1558', 'f1559', 'f1560', 'f1561', 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'f1214', 'f1215', 'f1216', 'f1217', 'f1218', 'f1219', 'f1220', 'f1221', 'f1222', 'f1223', 'f1224', 'f1225', 'f1226', 'f1227', 'f1228', 'f1229', 'f1230', 'f1231', 'f1232', 'f1233', 'f1234', 'f1235', 'f1236', 'f1237', 'f1238', 'f1239', 'f1240', 'f1241', 'f1242', 'f1243', 'f1244', 'f1245', 'f1246', 'f1247', 'f1248', 'f1249', 'f1250', 'f1251', 'f1252', 'f1253', 'f1254', 'f1255', 'f1256', 'f1257', 'f1258', 'f1259', 'f1260', 'f1261', 'f1262', 'f1263', 'f1264', 'f1265', 'f1266', 'f1267', 'f1268', 'f1269', 'f1270', 'f1271', 'f1272', 'f1273', 'f1274', 'f1275', 'f1276', 'f1277', 'f1278', 'f1279', 'f1280', 'f1281', 'f1282', 'f1283', 'f1284', 'f1285', 'f1286', 'f1287', 'f1288', 'f1289', 'f1290', 'f1291', 'f1292', 'f1293', 'f1294', 'f1295', 'f1296', 'f1297', 'f1298', 'f1299', 'f1300', 'f1301', 'f1302', 'f1303', 'f1304', 'f1305', 'f1306', 'f1307', 'f1308', 'f1309', 'f1310', 'f1311', 'f1312', 'f1313', 'f1314', 'f1315', 'f1316', 'f1317', 'f1318', 'f1319', 'f1320', 'f1321', 'f1322', 'f1323', 'f1324', 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'f1436', 'f1437', 'f1438', 'f1439', 'f1440', 'f1441', 'f1442', 'f1443', 'f1444', 'f1445', 'f1446', 'f1447', 'f1448', 'f1449', 'f1450', 'f1451', 'f1452', 'f1453', 'f1454', 'f1455', 'f1456', 'f1457', 'f1458', 'f1459', 'f1460', 'f1461', 'f1462', 'f1463', 'f1464', 'f1465', 'f1466', 'f1467', 'f1468', 'f1469', 'f1470', 'f1471', 'f1472', 'f1473', 'f1474', 'f1475', 'f1476', 'f1477', 'f1478', 'f1479', 'f1480', 'f1481', 'f1482', 'f1483', 'f1484', 'f1485', 'f1486', 'f1487', 'f1488', 'f1489', 'f1490', 'f1491', 'f1492', 'f1493', 'f1494', 'f1495', 'f1496', 'f1497', 'f1498', 'f1499', 'f1500', 'f1501', 'f1502', 'f1503', 'f1504', 'f1505', 'f1506', 'f1507', 'f1508', 'f1509', 'f1510', 'f1511', 'f1512', 'f1513', 'f1514', 'f1515', 'f1516', 'f1517', 'f1518', 'f1519', 'f1520', 'f1521', 'f1522', 'f1523', 'f1524', 'f1525', 'f1526', 'f1527', 'f1528', 'f1529', 'f1530', 'f1531', 'f1532', 'f1533', 'f1534', 'f1535', 'f1536', 'f1537', 'f1538', 'f1539', 'f1540', 'f1541', 'f1542', 'f1543', 'f1544', 'f1545', 'f1546', 'f1547', 'f1548', 'f1549', 'f1550', 'f1551', 'f1552', 'f1553', 'f1554', 'f1555', 'f1556', 'f1557', 'f1558', 'f1559', 'f1560', 'f1561', 'f1562', 'f1563', 'f1564', 'f1565', 'f1566', 'f1567', 'f1568', 'f1569', 'f1570', 'f1571', 'f1572', 'f1573', 'f1574', 'f1575', 'f1576', 'f1577', 'f1578', 'f1579', 'f1580', 'f1581', 'f1582', 'f1583', 'f1584', 'f1585', 'f1586', 'f1587', 'f1588', 'f1589', 'f1590', 'f1591', 'f1592', 'f1593', 'f1594', 'f1595', 'f1596', 'f1597', 'f1598', 'f1599', 'f1600', 'f1601', 'f1602', 'f1603', 'f1604', 'f1605', 'f1606', 'f1607', 'f1608', 'f1609', 'f1610', 'f1611', 'f1612', 'f1613', 'f1614', 'f1615', 'f1616', 'f1617', 'f1618', 'f1619', 'f1620', 'f1621', 'f1622', 'f1623', 'f1624', 'f1625', 'f1626', 'f1627', 'f1628', 'f1629', 'f1630', 'f1631', 'f1632', 'f1633', 'f1634', 'f1635', 'f1636', 'f1637', 'f1638', 'f1639', 'f1640', 'f1641', 'f1642', 'f1643', 'f1644', 'f1645', 'f1646', 'f1647', 'f1648', 'f1649', 'f1650', 'f1651', 'f1652', 'f1653', 'f1654', 'f1655', 'f1656', 'f1657', 'f1658', 'f1659', 'f1660', 'f1661', 'f1662', 'f1663', 'f1664', 'f1665', 'f1666', 'f1667', 'f1668', 'f1669', 'f1670', 'f1671', 'f1672', 'f1673', 'f1674', 'f1675', 'f1676', 'f1677', 'f1678', 'f1679', 'f1680', 'f1681', 'f1682', 'f1683', 'f1684', 'f1685', 'f1686', 'f1687', 'f1688', 'f1689', 'f1690', 'f1691', 'f1692', 'f1693', 'f1694', 'f1695', 'f1696', 'f1697', 'f1698', 'f1699', 'f1700', 'f1701', 'f1702', 'f1703', 'f1704', 'f1705', 'f1706', 'f1707', 'f1708', 'f1709', 'f1710', 'f1711', 'f1712', 'f1713', 'f1714', 'f1715', 'f1716', 'f1717', 'f1718', 'f1719', 'f1720', 'f1721', 'f1722', 'f1723', 'f1724', 'f1725', 'f1726', 'f1727', 'f1728', 'f1729', 'f1730', 'f1731', 'f1732', 'f1733', 'f1734', 'f1735', 'f1736', 'f1737', 'f1738', 'f1739', 'f1740', 'f1741', 'f1742', 'f1743', 'f1744', 'f1745', 'f1746', 'f1747', 'f1748', 'f1749', 'f1750', 'f1751', 'f1752', 'f1753', 'f1754', 'f1755', 'f1756', 'f1757', 'f1758', 'f1759', 'f1760', 'f1761', 'f1762', 'f1763', 'f1764', 'f1765', 'f1766', 'f1767', 'f1768', 'f1769', 'f1770', 'f1771', 'f1772', 'f1773', 'f1774', 'f1775', 'f1776', 'f1777', 'f1778', 'f1779', 'f1780', 'f1781', 'f1782', 'f1783', 'f1784', 'f1785', 'f1786', 'f1787', 'f1788', 'f1789', 'f1790', 'f1791', 'f1792', 'f1793', 'f1794', 'f1795', 'f1796', 'f1797', 'f1798', 'f1799', 'f1800', 'f1801', 'f1802', 'f1803', 'f1804', 'f1805', 'f1806', 'f1807', 'f1808', 'f1809', 'f1810', 'f1811', 'f1812', 'f1813', 'f1814', 'f1815', 'f1816', 'f1817', 'f1818', 'f1819', 'f1820', 'f1821', 'f1822', 'f1823', 'f1824', 'f1825', 'f1826', 'f1827', 'f1828', 'f1829', 'f1830', 'f1831', 'f1832', 'f1833', 'f1834', 'f1835', 'f1836', 'f1837', 'f1838', 'f1839', 'f1840', 'f1841', 'f1842', 'f1843', 'f1844', 'f1845', 'f1846', 'f1847', 'f1848', 'f1849', 'f1850', 'f1851', 'f1852', 'f1853', 'f1854', 'f1855', 'f1856', 'f1857', 'f1858', 'f1859', 'f1860', 'f1861', 'f1862', 'f1863', 'f1864', 'f1865', 'f1866', 'f1867', 'f1868', 'f1869', 'f1870', 'f1871', 'f1872', 'f1873', 'f1874', 'f1875', 'f1876', 'f1877', 'f1878', 'f1879', 'f1880', 'f1881', 'f1882', 'f1883', 'f1884', 'f1885', 'f1886', 'f1887', 'f1888', 'f1889', 'f1890', 'f1891', 'f1892', 'f1893', 'f1894', 'f1895', 'f1896', 'f1897', 'f1898', 'f1899', 'f1900', 'f1901', 'f1902', 'f1903', 'f1904', 'f1905', 'f1906', 'f1907', 'f1908', 'f1909', 'f1910', 'f1911', 'f1912', 'f1913', 'f1914', 'f1915', 'f1916', 'f1917', 'f1918', 'f1919', 'f1920', 'f1921', 'f1922', 'f1923', 'f1924', 'f1925', 'f1926', 'f1927', 'f1928', 'f1929', 'f1930', 'f1931', 'f1932', 'f1933', 'f1934', 'f1935', 'f1936', 'f1937', 'f1938', 'f1939', 'f1940', 'f1941', 'f1942', 'f1943', 'f1944', 'f1945', 'f1946', 'f1947', 'f1948', 'f1949', 'f1950', 'f1951', 'f1952', 'f1953', 'f1954', 'f1955', 'f1956', 'f1957', 'f1958', 'f1959', 'f1960', 'f1961', 'f1962', 'f1963', 'f1964', 'f1965', 'f1966', 'f1967', 'f1968', 'f1969', 'f1970', 'f1971', 'f1972', 'f1973', 'f1974', 'f1975', 'f1976', 'f1977', 'f1978', 'f1979', 'f1980', 'f1981', 'f1982', 'f1983', 'f1984', 'f1985', 'f1986', 'f1987', 'f1988', 'f1989', 'f1990', 'f1991', 'f1992', 'f1993', 'f1994', 'f1995', 'f1996', 'f1997', 'f1998', 'f1999', 'f2000', 'f2001', 'f2002', 'f2003', 'f2004', 'f2005', 'f2006', 'f2007', 'f2008', 'f2009', 'f2010', 'f2011', 'f2012', 'f2013', 'f2014', 'f2015', 'f2016', 'f2017', 'f2018', 'f2019', 'f2020', 'f2021', 'f2022', 'f2023', 'f2024', 'f2025', 'f2026', 'f2027', 'f2028', 'f2029', 'f2030', 'f2031', 'f2032', 'f2033', 'f2034', 'f2035', 'f2036', 'f2037', 'f2038', 'f2039', 'f2040', 'f2041', 'f2042', 'f2043', 'f2044', 'f2045', 'f2046', 'f2047', 'f2048', 'f2049', 'f2050', 'f2051', 'f2052', 'f2053', 'f2054', 'f2055', 'f2056', 'f2057', 'f2058', 'f2059', 'f2060', 'f2061', 'f2062', 'f2063', 'f2064', 'f2065', 'f2066', 'f2067', 'f2068', 'f2069', 'f2070', 'f2071', 'f2072', 'f2073', 'f2074', 'f2075', 'f2076', 'f2077', 'f2078', 'f2079', 'f2080', 'f2081', 'f2082', 'f2083', 'f2084', 'f2085', 'f2086', 'f2087', 'f2088', 'f2089', 'f2090', 'f2091', 'f2092', 'f2093', 'f2094', 'f2095', 'f2096', 'f2097', 'f2098', 'f2099', 'f2100', 'f2101', 'f2102', 'f2103', 'f2104', 'f2105', 'f2106', 'f2107', 'f2108', 'f2109', 'f2110', 'f2111', 'f2112', 'f2113', 'f2114', 'f2115', 'f2116', 'f2117', 'f2118', 'f2119', 'f2120', 'f2121', 'f2122', 'f2123', 'f2124', 'f2125', 'f2126', 'f2127', 'f2128', 'f2129', 'f2130', 'f2131', 'f2132', 'f2133', 'f2134', 'f2135', 'f2136', 'f2137', 'f2138', 'f2139', 'f2140', 'f2141', 'f2142', 'f2143', 'f2144', 'f2145', 'f2146', 'f2147', 'f2148', 'f2149', 'f2150', 'f2151', 'f2152', 'f2153', 'f2154', 'f2155', 'f2156', 'f2157', 'f2158', 'f2159', 'f2160', 'f2161', 'f2162', 'f2163', 'f2164', 'f2165', 'f2166', 'f2167', 'f2168', 'f2169', 'f2170', 'f2171', 'f2172', 'f2173', 'f2174', 'f2175', 'f2176', 'f2177', 'f2178', 'f2179', 'f2180', 'f2181', 'f2182', 'f2183', 'f2184', 'f2185', 'f2186', 'f2187', 'f2188', 'f2189', 'f2190', 'f2191', 'f2192', 'f2193', 'f2194', 'f2195', 'f2196', 'f2197', 'f2198', 'f2199', 'f2200', 'f2201', 'f2202', 'f2203', 'f2204', 'f2205', 'f2206', 'f2207', 'f2208', 'f2209', 'f2210', 'f2211', 'f2212', 'f2213', 'f2214', 'f2215', 'f2216', 'f2217', 'f2218', 'f2219', 'f2220', 'f2221', 'f2222', 'f2223', 'f2224', 'f2225', 'f2226', 'f2227', 'f2228', 'f2229', 'f2230', 'f2231', 'f2232', 'f2233', 'f2234', 'f2235', 'f2236', 'f2237', 'f2238', 'f2239', 'f2240', 'f2241', 'f2242', 'f2243', 'f2244', 'f2245', 'f2246', 'f2247', 'f2248', 'f2249', 'f2250', 'f2251', 'f2252', 'f2253', 'f2254', 'f2255', 'f2256', 'f2257', 'f2258', 'f2259', 'f2260', 'f2261', 'f2262', 'f2263', 'f2264', 'f2265', 'f2266', 'f2267', 'f2268', 'f2269', 'f2270', 'f2271', 'f2272', 'f2273', 'f2274', 'f2275', 'f2276', 'f2277', 'f2278', 'f2279', 'f2280', 'f2281', 'f2282', 'f2283', 'f2284', 'f2285', 'f2286', 'f2287', 'f2288', 'f2289', 'f2290', 'f2291', 'f2292', 'f2293', 'f2294', 'f2295', 'f2296', 'f2297', 'f2298', 'f2299', 'f2300', 'f2301', 'f2302', 'f2303', 'f2304', 'f2305', 'f2306', 'f2307', 'f2308', 'f2309', 'f2310', 'f2311', 'f2312', 'f2313', 'f2314', 'f2315', 'f2316', 'f2317', 'f2318', 'f2319', 'f2320', 'f2321', 'f2322', 'f2323', 'f2324', 'f2325', 'f2326', 'f2327', 'f2328', 'f2329', 'f2330', 'f2331', 'f2332', 'f2333', 'f2334', 'f2335', 'f2336', 'f2337', 'f2338', 'f2339', 'f2340', 'f2341', 'f2342', 'f2343', 'f2344', 'f2345', 'f2346', 'f2347', 'f2348', 'f2349', 'f2350', 'f2351', 'f2352', 'f2353', 'f2354', 'f2355', 'f2356', 'f2357', 'f2358', 'f2359', 'f2360', 'f2361', 'f2362', 'f2363', 'f2364', 'f2365', 'f2366', 'f2367', 'f2368', 'f2369', 'f2370', 'f2371', 'f2372', 'f2373', 'f2374', 'f2375', 'f2376', 'f2377', 'f2378', 'f2379', 'f2380', 'f2381', 'f2382', 'f2383', 'f2384', 'f2385', 'f2386', 'f2387', 'f2388', 'f2389', 'f2390', 'f2391', 'f2392', 'f2393', 'f2394', 'f2395', 'f2396', 'f2397', 'f2398', 'f2399', 'f2400', 'f2401', 'f2402', 'f2403', 'f2404', 'f2405', 'f2406', 'f2407', 'f2408', 'f2409', 'f2410', 'f2411', 'f2412', 'f2413', 'f2414', 'f2415', 'f2416', 'f2417', 'f2418', 'f2419', 'f2420', 'f2421', 'f2422', 'f2423', 'f2424', 'f2425', 'f2426', 'f2427', 'f2428', 'f2429', 'f2430', 'f2431', 'f2432', 'f2433', 'f2434', 'f2435', 'f2436', 'f2437', 'f2438', 'f2439', 'f2440', 'f2441', 'f2442', 'f2443', 'f2444', 'f2445', 'f2446', 'f2447', 'f2448', 'f2449', 'f2450', 'f2451', 'f2452', 'f2453', 'f2454', 'f2455', 'f2456', 'f2457', 'f2458', 'f2459', 'f2460', 'f2461', 'f2462', 'f2463', 'f2464', 'f2465', 'f2466', 'f2467', 'f2468', 'f2469', 'f2470', 'f2471', 'f2472', 'f2473', 'f2474', 'f2475', 'f2476', 'f2477', 'f2478', 'f2479', 'f2480', 'f2481', 'f2482', 'f2483', 'f2484', 'f2485', 'f2486', 'f2487', 'f2488', 'f2489', 'f2490', 'f2491', 'f2492', 'f2493', 'f2494', 'f2495', 'f2496', 'f2497', 'f2498', 'f2499', 'f2500', 'f2501', 'f2502', 'f2503', 'f2504', 'f2505', 'f2506', 'f2507', 'f2508', 'f2509', 'f2510', 'f2511', 'f2512', 'f2513', 'f2514', 'f2515', 'f2516', 'f2517', 'f2518', 'f2519', 'f2520', 'f2521', 'f2522', 'f2523', 'f2524', 'f2525', 'f2526', 'f2527', 'f2528', 'f2529', 'f2530', 'f2531', 'f2532', 'f2533', 'f2534', 'f2535', 'f2536', 'f2537', 'f2538', 'f2539', 'f2540', 'f2541', 'f2542', 'f2543', 'f2544', 'f2545', 'f2546', 'f2547', 'f2548', 'f2549', 'f2550', 'f2551', 'f2552', 'f2553', 'f2554', 'f2555', 'f2556', 'f2557', 'f2558', 'f2559', 'f2560']\n",
      "expected f2569, f2567, f2575, f2578, f2572, f2562, f2577, f2566, f2571, f2565, f2568, f2563, f2580, f2576, f2564, f2570, f2579, f2573, f2574, f2561 in input data\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:57:14,615:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.368852 9: 0.372951 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.368852 14: 0.364754 15: 0.377049 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.368852 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.377049 29: 0.377049 30: 0.377049 31: 0.377049 32: 0.377049 33: 0.377049 34: 0.377049 35: 0.372951 36: 0.377049 37: 0.377049 38: 0.377049 39: 0.377049 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [13, 4, 4, 13, 4, 13, 37, 7, 12, 0, 10, 4, 4, 1, 3, 8, 4, 2, 4, 4, 4, 4, 1, 0, 8, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 1, 3, 2, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4]\n",
      "\tWeights: [ 0.04  0.06  0.06  0.08  0.58  0.    0.    0.02  0.04  0.    0.02  0.\n",
      "  0.02  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 13) (1, 21) (1, 37) (1, 39) (1, 40) (1, 65) (1, 67) (1, 69) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:14,623:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:57:14,624:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.250947 seconds\n",
      "[INFO] [2016-08-16 07:57:14,626:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:57:15,355:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 198. configuration. Duration: 5.916148; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:57:15,728:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 163 training points for SMAC.\n",
      "[INFO] [2016-08-16 07:57:32,097:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 16.3671 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:57:32,102:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 199. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:32,104:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 5\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.16521703672\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:32,638:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 199. configuration. Duration: 0.487921; loss: 0.676230; status 1; additional run info: ;duration: 0.48792099952697754;num_run:00199 \n",
      "[INFO] [2016-08-16 07:57:32,645:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 200. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:32,647:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: True\n",
      "  classifier:extra_trees:criterion, Value: entropy\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 2.74801246511\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 5\n",
      "  classifier:extra_trees:min_samples_split, Value: 6\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 60.1843449141\n",
      "  preprocessor:select_percentile_classification:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:57:32,699:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:57:32,753:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:57:32,834:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:57:32,847:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 200. configuration. Duration: 0.163840; loss: 0.807377; status 1; additional run info: ;duration: 0.16383981704711914;num_run:00200 \n",
      "[INFO] [2016-08-16 07:57:32,853:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 201. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:32,856:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 3\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.132391803275\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:33,410:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 201. configuration. Duration: 0.510169; loss: 0.659836; status 1; additional run info: ;duration: 0.5101687908172607;num_run:00201 \n",
      "[INFO] [2016-08-16 07:57:33,416:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 202. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:33,417:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 0.000214954870245\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 363\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.291204146499\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 7\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 3\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 9\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 27\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:33,880:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 202. configuration. Duration: 0.431120; loss: 0.750000; status 1; additional run info: ;duration: 0.4311203956604004;num_run:00202 \n",
      "[INFO] [2016-08-16 07:57:33,886:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 203. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:33,887:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 6\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.311045418818\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:57:34,415:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 203. configuration. Duration: 0.483259; loss: 0.651639; status 1; additional run info: ;duration: 0.4832592010498047;num_run:00203 \n",
      "[INFO] [2016-08-16 07:57:34,421:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 204. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:34,422:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 29.038915074\n",
      "  classifier:bernoulli_nb:fit_prior, Value: True\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00140072631494\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:57:34,472:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 204. configuration. Duration: 0.018190; loss: 0.860656; status 1; additional run info: ;duration: 0.01819014549255371;num_run:00204 \n",
      "[INFO] [2016-08-16 07:57:34,478:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 205. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:34,480:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 6\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:34,614:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.368852 9: 0.372951 10: 0.377049 11: 0.377049 12: 0.377049 13: 0.368852 14: 0.364754 15: 0.377049 16: 0.372951 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.368852 23: 0.372951 24: 0.377049 25: 0.377049 26: 0.377049 27: 0.377049 28: 0.377049 29: 0.377049 30: 0.377049 31: 0.377049 32: 0.377049 33: 0.377049 34: 0.377049 35: 0.372951 36: 0.377049 37: 0.377049 38: 0.377049 39: 0.377049 40: 0.381148 41: 0.381148 42: 0.381148 43: 0.381148 44: 0.381148 45: 0.381148 46: 0.381148 47: 0.381148 48: 0.381148 49: 0.381148\n",
      "\tMembers: [12, 4, 4, 12, 4, 12, 36, 6, 11, 0, 9, 4, 4, 1, 3, 7, 4, 2, 4, 4, 4, 4, 1, 0, 7, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 1, 3, 2, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4]\n",
      "\tWeights: [ 0.04  0.06  0.06  0.08  0.58  0.    0.02  0.04  0.    0.02  0.    0.02\n",
      "  0.06  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 13) (1, 21) (1, 37) (1, 39) (1, 40) (1, 65) (1, 67) (1, 69) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:34,619:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.381148\n",
      "[INFO] [2016-08-16 07:57:34,621:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.925994 seconds\n",
      "[INFO] [2016-08-16 07:57:34,623:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:57:35,007:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 205. configuration. Duration: 0.483058; loss: 0.651639; status 1; additional run info: ;duration: 0.48305845260620117;num_run:00205 \n",
      "[INFO] [2016-08-16 07:57:35,013:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 206. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:35,015:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gaussian_nb\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0124414542936\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:57:35,064:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 206. configuration. Duration: 0.019117; loss: 0.975410; status 1; additional run info: ;duration: 0.019117116928100586;num_run:00206 \n",
      "[INFO] [2016-08-16 07:57:35,070:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 207. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:35,071:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 5\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000410463630695\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:57:35,596:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 207. configuration. Duration: 0.480430; loss: 0.676230; status 1; additional run info: ;duration: 0.48043012619018555;num_run:00207 \n",
      "[INFO] [2016-08-16 07:57:35,603:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 208. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:35,604:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 0.716784929831\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 18\n",
      "  classifier:random_forest:min_samples_split, Value: 2\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 4\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 2\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 6\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 98\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:36,009:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 208. configuration. Duration: 0.363225; loss: 0.778689; status 1; additional run info: ;duration: 0.36322498321533203;num_run:00208 \n",
      "[INFO] [2016-08-16 07:57:36,015:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 209. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:36,016:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:36,548:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 209. configuration. Duration: 0.487857; loss: 0.672131; status 1; additional run info: ;duration: 0.4878566265106201;num_run:00209 \n",
      "[INFO] [2016-08-16 07:57:36,554:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 210. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:36,555:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: entropy\n",
      "  classifier:decision_tree:max_depth, Value: 1.53828948588\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 12\n",
      "  classifier:decision_tree:min_samples_split, Value: 6\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.309344299591\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: cosine\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 112\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: max\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:36,596:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 210. configuration. Duration: 0.011760; loss: 0.680328; status 1; additional run info: ;duration: 0.011759519577026367;num_run:00210 \n",
      "[INFO] [2016-08-16 07:57:36,602:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 211. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:36,604:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 7\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:57:36,638:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:57:36,692:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:57:36,773:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:57:37,126:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 211. configuration. Duration: 0.475494; loss: 0.668033; status 1; additional run info: ;duration: 0.475494384765625;num_run:00211 \n",
      "[INFO] [2016-08-16 07:57:37,132:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 212. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:37,134:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: k_nearest_neighbors\n",
      "  classifier:k_nearest_neighbors:n_neighbors, Value: 4\n",
      "  classifier:k_nearest_neighbors:p, Value: 1\n",
      "  classifier:k_nearest_neighbors:weights, Value: uniform\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:gamma, Value: 0.0107801354251\n",
      "  preprocessor:kernel_pca:kernel, Value: rbf\n",
      "  preprocessor:kernel_pca:n_components, Value: 825\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:37,986:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 212. configuration. Duration: 0.808815; loss: 0.754098; status 1; additional run info: ;duration: 0.8088150024414062;num_run:00212 \n",
      "[INFO] [2016-08-16 07:57:37,992:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 213. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:37,994:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 4\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:38,591:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 213. configuration. Duration: 0.549307; loss: 0.672131; status 1; additional run info: ;duration: 0.5493066310882568;num_run:00213 \n",
      "[INFO] [2016-08-16 07:57:38,597:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 214. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:38,598:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: entropy\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 3.25542470077\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 9\n",
      "  classifier:extra_trees:min_samples_split, Value: 7\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:57:38,896:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.368852 9: 0.372951 10: 0.364754 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.368852 16: 0.368852 17: 0.368852 18: 0.368852 19: 0.368852 20: 0.364754 21: 0.364754 22: 0.368852 23: 0.368852 24: 0.364754 25: 0.364754 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.364754 31: 0.364754 32: 0.364754 33: 0.364754 34: 0.364754 35: 0.364754 36: 0.364754 37: 0.364754 38: 0.364754 39: 0.368852 40: 0.368852 41: 0.368852 42: 0.368852 43: 0.364754 44: 0.364754 45: 0.364754 46: 0.364754 47: 0.364754 48: 0.364754 49: 0.364754\n",
      "\tMembers: [10, 3, 3, 10, 3, 10, 32, 4, 9, 30, 9, 30, 43, 3, 3, 3, 3, 3, 3, 32, 3, 5, 32, 3, 3, 4, 9, 3, 10, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 25, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4]\n",
      "\tWeights: [ 0.    0.02  0.    0.62  0.06  0.02  0.    0.    0.    0.06  0.08  0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.04  0.    0.06  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 37) (1, 40) (1, 65) (1, 67) (1, 73) (1, 79) (1, 115) (1, 143) (1, 149) (1, 183)\n",
      "[INFO] [2016-08-16 07:57:38,902:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.364754\n",
      "[INFO] [2016-08-16 07:57:38,903:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.269057 seconds\n",
      "[INFO] [2016-08-16 07:57:38,906:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (202)!.\n",
      "[INFO] [2016-08-16 07:57:38,907:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (202)!\n",
      "[INFO] [2016-08-16 07:57:38,911:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 214. configuration. Duration: 0.273234; loss: 0.704918; status 1; additional run info: ;duration: 0.27323365211486816;num_run:00214 \n",
      "[ERROR] [2016-08-16 07:57:38,916:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:57:38,917:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 215. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:38,919:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 6\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[ERROR] [2016-08-16 07:57:38,976:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:57:39,063:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:57:39,491:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 215. configuration. Duration: 0.523072; loss: 0.651639; status 1; additional run info: ;duration: 0.5230720043182373;num_run:00215 \n",
      "[INFO] [2016-08-16 07:57:39,498:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 216. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:39,500:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 1933.67081447\n",
      "  classifier:libsvm_svc:gamma, Value: 0.00190197303202\n",
      "  classifier:libsvm_svc:kernel, Value: rbf\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: False\n",
      "  classifier:libsvm_svc:tol, Value: 0.00352610701893\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 8\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 1\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 4\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 12\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:57:39,717:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 216. configuration. Duration: 0.183862; loss: 0.786885; status 1; additional run info: ;duration: 0.18386220932006836;num_run:00216 \n",
      "[INFO] [2016-08-16 07:57:39,724:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 217. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:39,725:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.091031215205\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 2\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 14\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 403\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.629802024309\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00217626677543\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: liblinear_svc_preprocessor\n",
      "  preprocessor:liblinear_svc_preprocessor:C, Value: 0.192329114009\n",
      "  preprocessor:liblinear_svc_preprocessor:dual, Constant: False\n",
      "  preprocessor:liblinear_svc_preprocessor:fit_intercept, Constant: True\n",
      "  preprocessor:liblinear_svc_preprocessor:intercept_scaling, Constant: 1\n",
      "  preprocessor:liblinear_svc_preprocessor:loss, Value: squared_hinge\n",
      "  preprocessor:liblinear_svc_preprocessor:multi_class, Constant: ovr\n",
      "  preprocessor:liblinear_svc_preprocessor:penalty, Constant: l1\n",
      "  preprocessor:liblinear_svc_preprocessor:tol, Value: 0.0489053657338\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:57:40,122:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 217. configuration. Duration: 0.365366; loss: 0.704918; status 1; additional run info: ;duration: 0.36536645889282227;num_run:00217 \n",
      "[INFO] [2016-08-16 07:57:40,129:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 218. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:40,132:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 0.0228037945327\n",
      "  classifier:sgd:average, Value: True\n",
      "  classifier:sgd:epsilon, Value: 0.000865315793256\n",
      "  classifier:sgd:eta0, Value: 0.00880683802423\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: invscaling\n",
      "  classifier:sgd:loss, Value: modified_huber\n",
      "  classifier:sgd:n_iter, Value: 846\n",
      "  classifier:sgd:penalty, Value: l2\n",
      "  classifier:sgd:power_t, Value: 0.426367179413\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: euclidean\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 185\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: median\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:40,892:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.372951 8: 0.368852 9: 0.372951 10: 0.364754 11: 0.372951 12: 0.364754 13: 0.368852 14: 0.368852 15: 0.368852 16: 0.368852 17: 0.364754 18: 0.364754 19: 0.364754 20: 0.364754 21: 0.364754 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.368852 32: 0.368852 33: 0.368852 34: 0.364754 35: 0.368852 36: 0.368852 37: 0.368852 38: 0.368852 39: 0.364754 40: 0.364754 41: 0.364754 42: 0.364754 43: 0.364754 44: 0.364754 45: 0.364754 46: 0.368852 47: 0.368852 48: 0.368852 49: 0.368852\n",
      "\tMembers: [10, 3, 3, 10, 3, 10, 31, 4, 9, 29, 9, 29, 3, 31, 3, 3, 3, 3, 3, 3, 3, 4, 31, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 4, 7, 3, 3, 3]\n",
      "\tWeights: [ 0.04  0.    0.06  0.62  0.06  0.    0.    0.02  0.    0.04  0.06  0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.04  0.    0.06  0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 21) (1, 39) (1, 40) (1, 65) (1, 69) (1, 73) (1, 79) (1, 143) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:40,899:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.368852\n",
      "[INFO] [2016-08-16 07:57:40,901:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.989160 seconds\n",
      "[INFO] [2016-08-16 07:57:40,905:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (206)!.\n",
      "[INFO] [2016-08-16 07:57:40,907:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (206)!\n",
      "[ERROR] [2016-08-16 07:57:40,917:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:57:40,977:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:57:41,056:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 218. configuration. Duration: 0.893092; loss: 0.745902; status 1; additional run info: ;duration: 0.8930916786193848;num_run:00218 \n",
      "[INFO] [2016-08-16 07:57:41,064:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 219. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:41,066:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: entropy\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 2.91631855297\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 12\n",
      "  classifier:extra_trees:min_samples_split, Value: 9\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000137277851742\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.0707963646551\n",
      "  preprocessor:select_rates:mode, Value: fpr\n",
      "  preprocessor:select_rates:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: normalize\n",
      "[ERROR] [2016-08-16 07:57:41,067:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "\n",
      "[INFO] [2016-08-16 07:57:41,299:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 219. configuration. Duration: 0.191408; loss: 0.717213; status 1; additional run info: ;duration: 0.1914076805114746;num_run:00219 \n",
      "[INFO] [2016-08-16 07:57:41,306:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 220. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:41,307:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: proj_logit\n",
      "  classifier:proj_logit:max_epochs, Value: 8\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:57:41,383:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 220. configuration. Duration: 0.036238; loss: 0.741803; status 1; additional run info: ;duration: 0.03623771667480469;num_run:00220 \n",
      "[INFO] [2016-08-16 07:57:41,391:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 221. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:41,393:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: entropy\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 3.31497888247\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 19\n",
      "  classifier:extra_trees:min_samples_split, Value: 12\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000655564718535\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.362197626727\n",
      "  preprocessor:select_rates:mode, Value: fwe\n",
      "  preprocessor:select_rates:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:57:41,620:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 221. configuration. Duration: 0.186989; loss: 0.725410; status 1; additional run info: ;duration: 0.18698930740356445;num_run:00221 \n",
      "[INFO] [2016-08-16 07:57:41,627:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 222. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:41,628:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 0.0721445006771\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: squared_hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 260\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00587244728904\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:57:42,391:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 222. configuration. Duration: 0.731141; loss: 0.774590; status 1; additional run info: ;duration: 0.7311410903930664;num_run:00222 \n",
      "[INFO] [2016-08-16 07:57:42,397:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 223. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:42,399:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: False\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 1.19707589764\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 4\n",
      "  classifier:random_forest:min_samples_split, Value: 18\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000230165604281\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: cosine\n",
      "  preprocessor:feature_agglomeration:linkage, Value: average\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 18\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: median\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:57:42,644:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 223. configuration. Duration: 0.204961; loss: 0.725410; status 1; additional run info: ;duration: 0.20496058464050293;num_run:00223 \n",
      "[INFO] [2016-08-16 07:57:42,651:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 224. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:42,652:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0331040310821\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 5\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 11\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 374\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.861562950466\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: pca\n",
      "  preprocessor:pca:keep_variance, Value: 0.635472587278\n",
      "  preprocessor:pca:whiten, Value: True\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:57:42,933:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.368852 43: 0.368852 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.368852 48: 0.368852 49: 0.372951\n",
      "\tMembers: [9, 3, 3, 9, 3, 9, 30, 9, 3, 2, 9, 30, 3, 3, 3, 3, 30, 2, 9, 3, 3, 3, 1, 3, 3, 3, 2, 3, 3, 9, 3, 3, 3, 3, 3, 3, 8, 3, 30, 1, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3]\n",
      "\tWeights: [ 0.    0.06  0.08  0.62  0.    0.    0.    0.    0.02  0.14  0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 37) (1, 39) (1, 40) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:42,938:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:57:42,940:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.026746 seconds\n",
      "[INFO] [2016-08-16 07:57:42,942:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (209)!.\n",
      "[INFO] [2016-08-16 07:57:42,944:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (209)!\n",
      "[ERROR] [2016-08-16 07:57:42,954:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:57:43,013:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:57:43,103:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:57:43,246:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 224. configuration. Duration: 0.559515; loss: 0.750000; status 1; additional run info: ;duration: 0.5595149993896484;num_run:00224 \n",
      "[INFO] [2016-08-16 07:57:43,252:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 225. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:43,254:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: False\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 3.69451504562\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 12\n",
      "  classifier:random_forest:min_samples_split, Value: 5\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: exp\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 108, in _ica_par\n",
      "    - g_wtx[:, np.newaxis] * W)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 55, in _sym_decorrelation\n",
      "    s, u = linalg.eigh(np.dot(W, W.T))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/linalg/decomp.py\", line 288, in eigh\n",
      "    a1 = _asarray_validated(a, check_finite=check_finite)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/_lib/_util.py\", line 187, in _asarray_validated\n",
      "    a = toarray(a)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/numpy/lib/function_base.py\", line 668, in asarray_chkfinite\n",
      "    \"array must not contain infs or NaNs\")\n",
      "ValueError: array must not contain infs or NaNs\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 36, in fit\n",
      "    raise ValueError(\"Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\")\n",
      "ValueError: Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:57:44,370:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 225. configuration. Duration: 1.111333; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:57:44,378:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 226. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:57:44,379:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.148996234212\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 8\n",
      "  classifier:gradient_boosting:max_features, Value: 2.36220206009\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 14\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 19\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 162\n",
      "  classifier:gradient_boosting:subsample, Value: 0.870347862583\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000283836810573\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:gamma, Value: 0.725350032904\n",
      "  preprocessor:kernel_pca:kernel, Value: rbf\n",
      "  preprocessor:kernel_pca:n_components, Value: 449\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:57:45,234:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.368852 43: 0.368852 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.368852 48: 0.368852 49: 0.372951\n",
      "\tMembers: [9, 3, 3, 9, 3, 9, 30, 9, 3, 2, 9, 30, 3, 3, 3, 3, 30, 2, 9, 3, 3, 3, 1, 3, 3, 3, 2, 3, 3, 9, 3, 3, 3, 3, 3, 3, 8, 3, 30, 1, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3]\n",
      "\tWeights: [ 0.    0.06  0.08  0.62  0.    0.    0.    0.    0.02  0.14  0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 37) (1, 39) (1, 40) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:45,240:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:57:45,242:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.292228 seconds\n",
      "[INFO] [2016-08-16 07:57:45,243:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run23\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:57:47,260:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:57:47,322:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:57:47,419:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:57:49,337:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.368852 43: 0.368852 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.368852 48: 0.368852 49: 0.372951\n",
      "\tMembers: [9, 3, 3, 9, 3, 9, 30, 9, 3, 2, 9, 30, 3, 3, 3, 3, 30, 2, 9, 3, 3, 3, 1, 3, 3, 3, 2, 3, 3, 9, 3, 3, 3, 3, 3, 3, 8, 3, 30, 1, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3]\n",
      "\tWeights: [ 0.    0.06  0.08  0.62  0.    0.    0.    0.    0.02  0.14  0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 37) (1, 39) (1, 40) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:49,343:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:57:49,344:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.088955 seconds\n",
      "[INFO] [2016-08-16 07:57:49,346:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:57:52,367:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 226. configuration. Duration: 7.831782; loss: 0.827869; status 1; additional run info: ;duration: 7.831782341003418;num_run:00226 \n",
      "[INFO] [2016-08-16 07:57:52,737:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 187 training points for SMAC.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run23\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:57:53,368:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:57:53,423:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:57:53,512:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:57:55,421:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.368852 43: 0.368852 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.368852 48: 0.368852 49: 0.372951\n",
      "\tMembers: [9, 3, 3, 9, 3, 9, 30, 9, 3, 2, 9, 30, 3, 3, 3, 3, 30, 2, 9, 3, 3, 3, 1, 3, 3, 3, 2, 3, 3, 9, 3, 3, 3, 3, 3, 3, 8, 3, 30, 1, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3]\n",
      "\tWeights: [ 0.    0.06  0.08  0.62  0.    0.    0.    0.    0.02  0.14  0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 37) (1, 39) (1, 40) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:57:55,427:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:57:55,428:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.064626 seconds\n",
      "[INFO] [2016-08-16 07:57:55,430:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:58:07,003:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 14.2643 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:58:07,008:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 227. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:07,009:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:07,505:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 227. configuration. Duration: 0.453510; loss: 0.647541; status 1; additional run info: ;duration: 0.4535098075866699;num_run:00227 \n",
      "[INFO] [2016-08-16 07:58:07,511:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 228. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:07,512:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 1.36569810232\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 464\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0162880404214\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 1.22361961968\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 127\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:08,410:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 228. configuration. Duration: 0.842628; loss: 1.016393; status 1; additional run info: ;duration: 0.8426275253295898;num_run:00228 \n",
      "[INFO] [2016-08-16 07:58:08,416:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 229. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:08,417:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:08,943:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 229. configuration. Duration: 0.482374; loss: 0.647541; status 1; additional run info: ;duration: 0.4823744297027588;num_run:00229 \n",
      "[INFO] [2016-08-16 07:58:08,949:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 230. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:08,950:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.253631551281\n",
      "  classifier:adaboost:max_depth, Value: 5\n",
      "  classifier:adaboost:n_estimators, Value: 68\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00724200852202\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 4.76648523265\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 2\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 6\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:09,282:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 230. configuration. Duration: 0.290014; loss: 0.709016; status 1; additional run info: ;duration: 0.29001426696777344;num_run:00230 \n",
      "[INFO] [2016-08-16 07:58:09,287:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 231. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:09,288:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.01\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run23\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:58:09,486:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:58:09,539:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:58:09,626:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:58:09,674:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:58:09,853:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 231. configuration. Duration: 0.510329; loss: 0.647541; status 1; additional run info: ;duration: 0.5103294849395752;num_run:00231 \n",
      "[INFO] [2016-08-16 07:58:09,860:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 232. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:09,861:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: proj_logit\n",
      "  classifier:proj_logit:max_epochs, Value: 14\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.134149183255\n",
      "  preprocessor:select_rates:mode, Value: fdr\n",
      "  preprocessor:select_rates:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:58:09,984:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 232. configuration. Duration: 0.078069; loss: 0.848361; status 1; additional run info: ;duration: 0.07806873321533203;num_run:00232 \n",
      "[INFO] [2016-08-16 07:58:09,993:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 233. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:09,995:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:10,645:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 233. configuration. Duration: 0.599414; loss: 0.647541; status 1; additional run info: ;duration: 0.5994138717651367;num_run:00233 \n",
      "[INFO] [2016-08-16 07:58:10,653:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 234. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:10,655:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 5.15456599113\n",
      "  classifier:libsvm_svc:coef0, Value: -0.444119623302\n",
      "  classifier:libsvm_svc:gamma, Value: 0.047531711626\n",
      "  classifier:libsvm_svc:kernel, Value: sigmoid\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: False\n",
      "  classifier:libsvm_svc:tol, Value: 0.0027244726977\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 10\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 8\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 20\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 71\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:11,171:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 234. configuration. Duration: 0.476181; loss: 0.852459; status 1; additional run info: ;duration: 0.4761812686920166;num_run:00234 \n",
      "[INFO] [2016-08-16 07:58:11,176:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 235. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:11,178:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00024395872174\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:11,771:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.372951 30: 0.372951 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.372951 36: 0.372951 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.368852 43: 0.368852 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.368852 48: 0.368852 49: 0.372951\n",
      "\tMembers: [9, 3, 3, 9, 3, 9, 29, 9, 3, 2, 9, 29, 3, 3, 3, 3, 29, 2, 9, 3, 3, 3, 1, 3, 3, 3, 2, 3, 3, 9, 3, 3, 3, 3, 3, 3, 8, 3, 29, 1, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3]\n",
      "\tWeights: [ 0.    0.06  0.08  0.62  0.    0.    0.    0.    0.02  0.14  0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 37) (1, 39) (1, 40) (1, 73) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:58:11,777:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:58:11,778:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.295777 seconds\n",
      "[INFO] [2016-08-16 07:58:11,780:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:58:11,878:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 235. configuration. Duration: 0.648618; loss: 0.647541; status 1; additional run info: ;duration: 0.6486175060272217;num_run:00235 \n",
      "[INFO] [2016-08-16 07:58:11,884:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 236. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:11,886:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 1829.01065174\n",
      "  classifier:libsvm_svc:gamma, Value: 0.558090372693\n",
      "  classifier:libsvm_svc:kernel, Value: rbf\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: True\n",
      "  classifier:libsvm_svc:tol, Value: 0.00577294880908\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000103490633032\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:kernel, Value: cosine\n",
      "  preprocessor:kernel_pca:n_components, Value: 637\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:13,500:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 236. configuration. Duration: 1.572980; loss: 0.868852; status 1; additional run info: ;duration: 1.5729801654815674;num_run:00236 \n",
      "[INFO] [2016-08-16 07:58:13,507:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 237. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:13,508:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run23\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:58:13,795:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:58:13,860:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:58:13,955:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:58:14,002:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:58:14,131:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 237. configuration. Duration: 0.567623; loss: 0.647541; status 1; additional run info: ;duration: 0.5676233768463135;num_run:00237 \n",
      "[INFO] [2016-08-16 07:58:14,139:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 238. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:14,140:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.128651484774\n",
      "  classifier:adaboost:max_depth, Value: 6\n",
      "  classifier:adaboost:n_estimators, Value: 384\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0350077160474\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:kernel, Value: cosine\n",
      "  preprocessor:kernel_pca:n_components, Value: 561\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:16,222:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.368852 36: 0.368852 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.368852 44: 0.368852 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [7, 2, 2, 7, 2, 7, 27, 7, 2, 1, 7, 27, 2, 2, 2, 2, 27, 1, 7, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 20, 2, 2, 2, 1, 6, 7, 27, 2, 2, 2, 25, 2, 1, 2, 2, 7, 2, 2]\n",
      "\tWeights: [ 0.    0.08  0.62  0.    0.    0.    0.02  0.16  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.\n",
      "  0.02  0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 39) (1, 40) (1, 73) (1, 79) (1, 113) (1, 143) (1, 149)\n",
      "[INFO] [2016-08-16 07:58:16,229:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:58:16,231:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.440774 seconds\n",
      "[INFO] [2016-08-16 07:58:16,234:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (227)!.\n",
      "[INFO] [2016-08-16 07:58:16,236:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (227)!\n",
      "[ERROR] [2016-08-16 07:58:16,248:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:58:16,317:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:58:16,421:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:58:16,473:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:58:18,570:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.368852 36: 0.368852 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.368852 44: 0.368852 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [7, 2, 2, 7, 2, 7, 26, 7, 2, 1, 7, 26, 2, 2, 2, 2, 26, 1, 7, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 20, 2, 2, 2, 1, 6, 7, 26, 2, 2, 2, 24, 2, 1, 2, 2, 7, 2, 2]\n",
      "\tWeights: [ 0.    0.08  0.62  0.    0.    0.    0.02  0.16  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.02\n",
      "  0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 39) (1, 40) (1, 73) (1, 79) (1, 119) (1, 143) (1, 149)\n",
      "[INFO] [2016-08-16 07:58:18,576:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:58:18,578:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.335383 seconds\n",
      "[INFO] [2016-08-16 07:58:18,580:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:58:25,288:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 238. configuration. Duration: 11.046431; loss: 0.741803; status 1; additional run info: ;duration: 11.046431303024292;num_run:00238 \n",
      "[INFO] [2016-08-16 07:58:25,698:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 195 training points for SMAC.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run24\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:58:26,620:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:58:26,679:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:58:26,768:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:58:26,812:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:58:28,640:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.368852 36: 0.368852 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.368852 44: 0.368852 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [7, 2, 2, 7, 2, 7, 26, 7, 2, 1, 7, 26, 2, 2, 2, 2, 26, 1, 7, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 20, 2, 2, 2, 1, 6, 7, 26, 2, 2, 2, 24, 2, 1, 2, 2, 7, 2, 2]\n",
      "\tWeights: [ 0.    0.08  0.62  0.    0.    0.    0.02  0.16  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.02\n",
      "  0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 39) (1, 40) (1, 73) (1, 79) (1, 119) (1, 143) (1, 149)\n",
      "[INFO] [2016-08-16 07:58:28,646:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:58:28,647:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.031518 seconds\n",
      "[INFO] [2016-08-16 07:58:28,649:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:58:39,293:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 13.5936 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:58:39,298:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 239. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:39,300:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: logcosh\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 108, in _ica_par\n",
      "    - g_wtx[:, np.newaxis] * W)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 55, in _sym_decorrelation\n",
      "    s, u = linalg.eigh(np.dot(W, W.T))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/linalg/decomp.py\", line 288, in eigh\n",
      "    a1 = _asarray_validated(a, check_finite=check_finite)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/_lib/_util.py\", line 187, in _asarray_validated\n",
      "    a = toarray(a)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/numpy/lib/function_base.py\", line 668, in asarray_chkfinite\n",
      "    \"array must not contain infs or NaNs\")\n",
      "ValueError: array must not contain infs or NaNs\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 36, in fit\n",
      "    raise ValueError(\"Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\")\n",
      "ValueError: Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:40,391:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 239. configuration. Duration: 1.084260; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:58:40,399:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 240. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:40,401:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 163\n",
      "  classifier:lda:shrinkage, Value: None\n",
      "  classifier:lda:tol, Value: 0.0137495531096\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.20284845772\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 73.2842036082\n",
      "  preprocessor:select_percentile_classification:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:58:40,448:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 240. configuration. Duration: 0.018744; loss: 0.872951; status 1; additional run info: ;duration: 0.018743515014648438;num_run:00240 \n",
      "[INFO] [2016-08-16 07:58:40,453:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 241. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:40,455:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00216585486193\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: logcosh\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 108, in _ica_par\n",
      "    - g_wtx[:, np.newaxis] * W)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 55, in _sym_decorrelation\n",
      "    s, u = linalg.eigh(np.dot(W, W.T))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/linalg/decomp.py\", line 288, in eigh\n",
      "    a1 = _asarray_validated(a, check_finite=check_finite)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/_lib/_util.py\", line 187, in _asarray_validated\n",
      "    a = toarray(a)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/numpy/lib/function_base.py\", line 668, in asarray_chkfinite\n",
      "    \"array must not contain infs or NaNs\")\n",
      "ValueError: array must not contain infs or NaNs\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 36, in fit\n",
      "    raise ValueError(\"Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\")\n",
      "ValueError: Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\n",
      "You are already timing task: index_run24\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:58:40,709:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:58:40,763:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:58:40,843:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:58:40,884:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:58:41,529:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 241. configuration. Duration: 1.067196; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:58:41,535:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 242. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:41,537:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: k_nearest_neighbors\n",
      "  classifier:k_nearest_neighbors:n_neighbors, Value: 90\n",
      "  classifier:k_nearest_neighbors:p, Value: 1\n",
      "  classifier:k_nearest_neighbors:weights, Value: distance\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 6\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 12\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 20\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 68\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:58:41,765:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 242. configuration. Duration: 0.194426; loss: 0.778689; status 1; additional run info: ;duration: 0.1944260597229004;num_run:00242 \n",
      "[INFO] [2016-08-16 07:58:41,771:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 243. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:41,773:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: logcosh\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 108, in _ica_par\n",
      "    - g_wtx[:, np.newaxis] * W)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 55, in _sym_decorrelation\n",
      "    s, u = linalg.eigh(np.dot(W, W.T))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/linalg/decomp.py\", line 288, in eigh\n",
      "    a1 = _asarray_validated(a, check_finite=check_finite)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/_lib/_util.py\", line 187, in _asarray_validated\n",
      "    a = toarray(a)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/numpy/lib/function_base.py\", line 668, in asarray_chkfinite\n",
      "    \"array must not contain infs or NaNs\")\n",
      "ValueError: array must not contain infs or NaNs\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 36, in fit\n",
      "    raise ValueError(\"Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\")\n",
      "ValueError: Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:42,558:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.368852 36: 0.368852 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.368852 44: 0.368852 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [7, 2, 2, 7, 2, 7, 26, 7, 2, 1, 7, 26, 2, 2, 2, 2, 26, 1, 7, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 20, 2, 2, 2, 1, 6, 7, 26, 2, 2, 2, 24, 2, 1, 2, 2, 7, 2, 2]\n",
      "\tWeights: [ 0.    0.08  0.62  0.    0.    0.    0.02  0.16  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.02\n",
      "  0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 39) (1, 40) (1, 73) (1, 79) (1, 119) (1, 143) (1, 149)\n",
      "[INFO] [2016-08-16 07:58:42,563:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:58:42,564:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.859799 seconds\n",
      "[INFO] [2016-08-16 07:58:42,566:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:58:42,868:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 243. configuration. Duration: 1.088918; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:58:42,876:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 244. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:42,878:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: multinomial_nb\n",
      "  classifier:multinomial_nb:alpha, Value: 26.5580727027\n",
      "  classifier:multinomial_nb:fit_prior, Value: False\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0297968694291\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 35.0478342302\n",
      "  preprocessor:select_percentile_classification:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:42,922:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 244. configuration. Duration: 0.014293; loss: 0.922131; status 1; additional run info: ;duration: 0.014292716979980469;num_run:00244 \n",
      "[INFO] [2016-08-16 07:58:42,928:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 245. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:42,930:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00220659936221\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: logcosh\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 108, in _ica_par\n",
      "    - g_wtx[:, np.newaxis] * W)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 55, in _sym_decorrelation\n",
      "    s, u = linalg.eigh(np.dot(W, W.T))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/linalg/decomp.py\", line 288, in eigh\n",
      "    a1 = _asarray_validated(a, check_finite=check_finite)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/_lib/_util.py\", line 187, in _asarray_validated\n",
      "    a = toarray(a)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/numpy/lib/function_base.py\", line 668, in asarray_chkfinite\n",
      "    \"array must not contain infs or NaNs\")\n",
      "ValueError: array must not contain infs or NaNs\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 36, in fit\n",
      "    raise ValueError(\"Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\")\n",
      "ValueError: Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:44,003:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 245. configuration. Duration: 1.067341; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:58:44,011:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 246. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:44,013:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: entropy\n",
      "  classifier:decision_tree:max_depth, Value: 0.761609154976\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 16\n",
      "  classifier:decision_tree:min_samples_split, Value: 10\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:44,150:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 246. configuration. Duration: 0.108585; loss: 0.754098; status 1; additional run info: ;duration: 0.10858488082885742;num_run:00246 \n",
      "[INFO] [2016-08-16 07:58:44,156:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 247. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:44,157:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: logcosh\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process pynisher function call:\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 33, in fit\n",
      "    self.preprocessor.fit(X)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 523, in fit\n",
      "    self._fit(X, compute_sources=False)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 479, in _fit\n",
      "    compute_sources=compute_sources, return_n_iter=True)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 335, in fastica\n",
      "    W, n_iter = _ica_par(X1, **kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 108, in _ica_par\n",
      "    - g_wtx[:, np.newaxis] * W)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/decomposition/fastica_.py\", line 55, in _sym_decorrelation\n",
      "    s, u = linalg.eigh(np.dot(W, W.T))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/linalg/decomp.py\", line 288, in eigh\n",
      "    a1 = _asarray_validated(a, check_finite=check_finite)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/scipy/_lib/_util.py\", line 187, in _asarray_validated\n",
      "    a = toarray(a)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/numpy/lib/function_base.py\", line 668, in asarray_chkfinite\n",
      "    \"array must not contain infs or NaNs\")\n",
      "ValueError: array must not contain infs or NaNs\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 249, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/opt/conda/lib/python3.5/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/pynisher/limit_function_call.py\", line 83, in subprocess_func\n",
      "    return_value = ((func(*args, **kwargs), 0))\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 148, in eval_holdout\n",
      "    loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss()\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/evaluation/holdout_evaluator.py\", line 59, in fit_predict_and_loss\n",
      "    self.model.fit(X_train, Y_train)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 62, in fit\n",
      "    init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/classification.py\", line 87, in pre_transform\n",
      "    X, y, fit_params=fit_params, init_params=init_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/base.py\", line 131, in pre_transform\n",
      "    X, fit_params = self.pipeline_._pre_transform(X, y, **fit_params)\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/sklearn/pipeline.py\", line 147, in _pre_transform\n",
      "    Xt = transform.fit(Xt, y, **fit_params_steps[name]) \\\n",
      "  File \"/opt/conda/lib/python3.5/site-packages/autosklearn/pipeline/components/feature_preprocessing/fast_ica.py\", line 36, in fit\n",
      "    raise ValueError(\"Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\")\n",
      "ValueError: Bug in scikit-learn: https://github.com/scikit-learn/scikit-learn/pull/2738\n",
      "You are already timing task: index_run24\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:58:44,587:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:58:44,635:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:58:44,709:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:58:44,745:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:58:45,224:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 247. configuration. Duration: 1.061876; loss: 2.000000; status 3; additional run info:  \n",
      "[INFO] [2016-08-16 07:58:45,231:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 248. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:45,232:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 7.05765591146\n",
      "  classifier:libsvm_svc:gamma, Value: 0.00998941511712\n",
      "  classifier:libsvm_svc:kernel, Value: rbf\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: False\n",
      "  classifier:libsvm_svc:tol, Value: 8.4086885902e-05\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0276695772285\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 20.0121367493\n",
      "  preprocessor:select_percentile_classification:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:45,314:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 248. configuration. Duration: 0.052881; loss: 0.872951; status 1; additional run info: ;duration: 0.05288124084472656;num_run:00248 \n",
      "[INFO] [2016-08-16 07:58:45,321:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 249. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:45,322:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0557671619111\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:45,865:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 249. configuration. Duration: 0.500574; loss: 0.647541; status 1; additional run info: ;duration: 0.5005738735198975;num_run:00249 \n",
      "[INFO] [2016-08-16 07:58:45,871:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 250. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:45,873:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: True\n",
      "  classifier:extra_trees:criterion, Value: entropy\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 2.96740124817\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 14\n",
      "  classifier:extra_trees:min_samples_split, Value: 14\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00168368290437\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: cosine\n",
      "  preprocessor:feature_agglomeration:linkage, Value: average\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 367\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: max\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:58:46,074:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 250. configuration. Duration: 0.165070; loss: 0.717213; status 1; additional run info: ;duration: 0.1650698184967041;num_run:00250 \n",
      "[INFO] [2016-08-16 07:58:46,081:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 251. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:46,083:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00140780731379\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:46,423:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.372951 32: 0.372951 33: 0.372951 34: 0.372951 35: 0.368852 36: 0.368852 37: 0.372951 38: 0.377049 39: 0.372951 40: 0.372951 41: 0.372951 42: 0.372951 43: 0.368852 44: 0.368852 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [7, 2, 2, 7, 2, 7, 26, 7, 2, 1, 7, 26, 2, 2, 2, 2, 26, 1, 7, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 20, 2, 2, 2, 1, 6, 7, 26, 2, 2, 2, 24, 2, 1, 2, 2, 7, 2, 2]\n",
      "\tWeights: [ 0.    0.08  0.62  0.    0.    0.    0.02  0.16  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.    0.    0.02\n",
      "  0.    0.08  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 39) (1, 40) (1, 73) (1, 79) (1, 119) (1, 143) (1, 149)\n",
      "[INFO] [2016-08-16 07:58:46,428:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:58:46,429:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 1.847049 seconds\n",
      "[INFO] [2016-08-16 07:58:46,431:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:58:46,617:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 251. configuration. Duration: 0.491348; loss: 0.647541; status 1; additional run info: ;duration: 0.4913480281829834;num_run:00251 \n",
      "[INFO] [2016-08-16 07:58:46,623:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 252. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:46,625:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 2.19779026094\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 166\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0417120368741\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.478991322012\n",
      "  preprocessor:select_rates:mode, Value: fdr\n",
      "  preprocessor:select_rates:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:58:46,780:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 252. configuration. Duration: 0.128166; loss: 0.864754; status 1; additional run info: ;duration: 0.12816572189331055;num_run:00252 \n",
      "[INFO] [2016-08-16 07:58:46,786:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 253. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:46,787:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0322275492407\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:47,282:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 253. configuration. Duration: 0.450714; loss: 0.647541; status 1; additional run info: ;duration: 0.4507136344909668;num_run:00253 \n",
      "[INFO] [2016-08-16 07:58:47,289:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 254. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:47,291:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 147\n",
      "  classifier:lda:shrinkage, Value: None\n",
      "  classifier:lda:tol, Value: 3.09181477593e-05\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:coef0, Value: -0.948574597272\n",
      "  preprocessor:kernel_pca:degree, Value: 5\n",
      "  preprocessor:kernel_pca:gamma, Value: 3.20669498205e-05\n",
      "  preprocessor:kernel_pca:kernel, Value: poly\n",
      "  preprocessor:kernel_pca:n_components, Value: 485\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:58:48,122:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 254. configuration. Duration: 0.762486; loss: 0.868852; status 1; additional run info: ;duration: 0.762486457824707;num_run:00254 \n",
      "[INFO] [2016-08-16 07:58:48,130:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 255. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:48,131:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: False\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 4.79442595134\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 1\n",
      "  classifier:random_forest:min_samples_split, Value: 20\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: deflation\n",
      "  preprocessor:fast_ica:fun, Value: cube\n",
      "  preprocessor:fast_ica:n_components, Value: 1051\n",
      "  preprocessor:fast_ica:whiten, Value: True\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "n_components is too large: it will be set to 9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run24\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:58:48,445:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:58:48,505:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:58:48,583:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:58:48,638:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:58:49,266:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 255. configuration. Duration: 1.096249; loss: 0.758197; status 1; additional run info: ;duration: 1.0962486267089844;num_run:00255 \n",
      "[INFO] [2016-08-16 07:58:49,274:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 256. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:49,277:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 0.0826346409249\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 88\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000159162512414\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 3.88711161466\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 9\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 16\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:49,561:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 256. configuration. Duration: 0.244519; loss: 0.786885; status 1; additional run info: ;duration: 0.24451923370361328;num_run:00256 \n",
      "[INFO] [2016-08-16 07:58:49,568:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 257. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:49,570:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.524223272018\n",
      "  classifier:adaboost:max_depth, Value: 2\n",
      "  classifier:adaboost:n_estimators, Value: 150\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00042196261322\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_rates\n",
      "  preprocessor:select_rates:alpha, Value: 0.259669948396\n",
      "  preprocessor:select_rates:mode, Value: fdr\n",
      "  preprocessor:select_rates:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:58:49,858:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 257. configuration. Duration: 0.240685; loss: 0.713115; status 1; additional run info: ;duration: 0.24068474769592285;num_run:00257 \n",
      "[INFO] [2016-08-16 07:58:49,866:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 258. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:49,867:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 0.000118686674731\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: squared_hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 5\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 0.934743328868\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 89\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:58:49,985:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 258. configuration. Duration: 0.050747; loss: 0.860656; status 1; additional run info: ;duration: 0.05074667930603027;num_run:00258 \n",
      "[INFO] [2016-08-16 07:58:49,993:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 259. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:49,995:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 4.35195219912\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 10\n",
      "  classifier:random_forest:min_samples_split, Value: 13\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: exp\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:58:50,404:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 259. configuration. Duration: 0.369153; loss: 0.750000; status 1; additional run info: ;duration: 0.3691532611846924;num_run:00259 \n",
      "[INFO] [2016-08-16 07:58:50,412:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 260. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:50,414:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 0.0841053273233\n",
      "  classifier:libsvm_svc:coef0, Value: -0.271867456316\n",
      "  classifier:libsvm_svc:degree, Value: 4\n",
      "  classifier:libsvm_svc:gamma, Value: 4.28871114284e-05\n",
      "  classifier:libsvm_svc:kernel, Value: poly\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: False\n",
      "  classifier:libsvm_svc:tol, Value: 2.17182091601e-05\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0104071405431\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 95.525679335\n",
      "  preprocessor:select_percentile_classification:score_func, Value: f_classif\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:50,486:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 260. configuration. Duration: 0.040026; loss: 0.860656; status 1; additional run info: ;duration: 0.040025949478149414;num_run:00260 \n",
      "[INFO] [2016-08-16 07:58:50,492:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 261. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:50,494:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.113956269486\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 4\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 18\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 307\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.667919040627\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00020133188394\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:58:50,609:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.368852 32: 0.364754 33: 0.364754 34: 0.368852 35: 0.364754 36: 0.364754 37: 0.368852 38: 0.368852 39: 0.368852 40: 0.368852 41: 0.368852 42: 0.372951 43: 0.372951 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.372951 48: 0.368852 49: 0.372951\n",
      "\tMembers: [7, 2, 2, 7, 2, 7, 25, 7, 2, 1, 7, 25, 2, 2, 2, 2, 25, 1, 7, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 39, 2, 2, 25, 2, 6, 2, 2, 7, 2, 2, 2, 23, 25, 1, 7]\n",
      "\tWeights: [ 0.    0.08  0.6   0.    0.    0.    0.02  0.16  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.1\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 39) (1, 40) (1, 73) (1, 79) (1, 143) (1, 149) (1, 211)\n",
      "[INFO] [2016-08-16 07:58:50,615:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:58:50,617:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.176121 seconds\n",
      "[INFO] [2016-08-16 07:58:50,619:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (240)!.\n",
      "[INFO] [2016-08-16 07:58:50,621:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (240)!\n",
      "[ERROR] [2016-08-16 07:58:50,632:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:58:50,694:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:58:50,787:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:58:50,833:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:58:51,067:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 261. configuration. Duration: 0.539521; loss: 0.704918; status 1; additional run info: ;duration: 0.5395214557647705;num_run:00261 \n",
      "[INFO] [2016-08-16 07:58:51,074:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 262. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:51,076:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 20234.6731671\n",
      "  classifier:libsvm_svc:gamma, Value: 0.103789295331\n",
      "  classifier:libsvm_svc:kernel, Value: rbf\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: True\n",
      "  classifier:libsvm_svc:tol, Value: 0.00198461388059\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:51,257:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 262. configuration. Duration: 0.149132; loss: 0.786885; status 1; additional run info: ;duration: 0.14913201332092285;num_run:00262 \n",
      "[INFO] [2016-08-16 07:58:51,265:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 263. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:51,267:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.793020482109\n",
      "  classifier:adaboost:max_depth, Value: 4\n",
      "  classifier:adaboost:n_estimators, Value: 254\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000441147213686\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 2.02065003018\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 1\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 4\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:52,363:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 263. configuration. Duration: 1.030640; loss: 0.782787; status 1; additional run info: ;duration: 1.030639886856079;num_run:00263 \n",
      "[INFO] [2016-08-16 07:58:52,371:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 264. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:52,373:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: liblinear_svc\n",
      "  classifier:liblinear_svc:C, Value: 2020.21054965\n",
      "  classifier:liblinear_svc:dual, Constant: False\n",
      "  classifier:liblinear_svc:fit_intercept, Constant: True\n",
      "  classifier:liblinear_svc:intercept_scaling, Constant: 1\n",
      "  classifier:liblinear_svc:loss, Value: squared_hinge\n",
      "  classifier:liblinear_svc:multi_class, Constant: ovr\n",
      "  classifier:liblinear_svc:penalty, Value: l2\n",
      "  classifier:liblinear_svc:tol, Value: 0.000212559610957\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: deflation\n",
      "  preprocessor:fast_ica:fun, Value: cube\n",
      "  preprocessor:fast_ica:n_components, Value: 544\n",
      "  preprocessor:fast_ica:whiten, Value: True\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "n_components is too large: it will be set to 9\n",
      "[INFO] [2016-08-16 07:58:52,516:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 264. configuration. Duration: 0.109359; loss: 0.721311; status 1; additional run info: ;duration: 0.1093590259552002;num_run:00264 \n",
      "[INFO] [2016-08-16 07:58:52,524:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 265. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:52,525:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.167602737112\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 5\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 7\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 137\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.156516674066\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: False\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 0.74438794527\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 14\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 20\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:58:52,808:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.368852 32: 0.364754 33: 0.364754 34: 0.368852 35: 0.364754 36: 0.364754 37: 0.368852 38: 0.368852 39: 0.368852 40: 0.368852 41: 0.368852 42: 0.372951 43: 0.372951 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.372951 48: 0.368852 49: 0.372951\n",
      "\tMembers: [7, 2, 2, 7, 2, 7, 25, 7, 2, 1, 7, 25, 2, 2, 2, 2, 25, 1, 7, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 39, 2, 2, 25, 2, 6, 2, 2, 7, 2, 2, 2, 23, 25, 1, 7]\n",
      "\tWeights: [ 0.    0.08  0.6   0.    0.    0.    0.02  0.16  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.1\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 39) (1, 40) (1, 73) (1, 79) (1, 143) (1, 149) (1, 211)"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "[INFO] [2016-08-16 07:58:52,815:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:58:52,817:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.189212 seconds\n",
      "[INFO] [2016-08-16 07:58:52,819:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:58:52,863:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 265. configuration. Duration: 0.295356; loss: 0.700820; status 1; additional run info: ;duration: 0.29535555839538574;num_run:00265 \n",
      "[INFO] [2016-08-16 07:58:52,871:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 266. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:58:52,873:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 2.0853229912e-06\n",
      "  classifier:sgd:average, Value: True\n",
      "  classifier:sgd:eta0, Value: 0.0938453015205\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: constant\n",
      "  classifier:sgd:loss, Value: hinge\n",
      "  classifier:sgd:n_iter, Value: 49\n",
      "  classifier:sgd:penalty, Value: l2\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 1.33646604904\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 654\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:58:53,394:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 266. configuration. Duration: 0.448127; loss: 0.745902; status 1; additional run info: ;duration: 0.44812655448913574;num_run:00266 \n",
      "[INFO] [2016-08-16 07:58:53,890:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 218 training points for SMAC.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run25\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:58:54,836:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:58:54,900:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:58:54,999:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:58:55,047:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:58:57,050:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.372951 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.364754 16: 0.368852 17: 0.368852 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.368852 32: 0.364754 33: 0.364754 34: 0.368852 35: 0.364754 36: 0.364754 37: 0.368852 38: 0.368852 39: 0.368852 40: 0.368852 41: 0.368852 42: 0.372951 43: 0.372951 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.372951 48: 0.368852 49: 0.372951\n",
      "\tMembers: [7, 2, 2, 7, 2, 7, 25, 7, 2, 1, 7, 25, 2, 2, 2, 2, 25, 1, 7, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 39, 2, 2, 25, 2, 6, 2, 2, 7, 2, 2, 2, 23, 25, 1, 7]\n",
      "\tWeights: [ 0.    0.08  0.6   0.    0.    0.    0.02  0.16  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.1\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 39) (1, 40) (1, 73) (1, 79) (1, 143) (1, 149) (1, 211)\n",
      "[INFO] [2016-08-16 07:58:57,056:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:58:57,058:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.226606 seconds\n",
      "[INFO] [2016-08-16 07:58:57,060:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:59:10,854:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 16.9621 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:59:10,860:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 267. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:10,862:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:11,499:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 267. configuration. Duration: 0.587581; loss: 0.647541; status 1; additional run info: ;duration: 0.5875813961029053;num_run:00267 \n",
      "[INFO] [2016-08-16 07:59:11,506:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 268. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:11,508:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: gini\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 0.590776897477\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 2\n",
      "  classifier:extra_trees:min_samples_split, Value: 3\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.102555970304\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:59:11,809:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 268. configuration. Duration: 0.254910; loss: 0.721311; status 1; additional run info: ;duration: 0.2549104690551758;num_run:00268 \n",
      "[INFO] [2016-08-16 07:59:11,816:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 269. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:11,818:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00178585503748\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:12,486:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 269. configuration. Duration: 0.615896; loss: 0.647541; status 1; additional run info: ;duration: 0.6158957481384277;num_run:00269 \n",
      "[INFO] [2016-08-16 07:59:12,493:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 270. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:12,495:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: bernoulli_nb\n",
      "  classifier:bernoulli_nb:alpha, Value: 0.600861419593\n",
      "  classifier:bernoulli_nb:fit_prior, Value: False\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: nystroem_sampler\n",
      "  preprocessor:nystroem_sampler:coef0, Value: 0.228849660174\n",
      "  preprocessor:nystroem_sampler:degree, Value: 3\n",
      "  preprocessor:nystroem_sampler:gamma, Value: 1.1730226195\n",
      "  preprocessor:nystroem_sampler:kernel, Value: poly\n",
      "  preprocessor:nystroem_sampler:n_components, Value: 842\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/kernel_approximation.py:463: UserWarning: n_components > n_samples. This is not possible.\n",
      "n_components was set to n_samples, which results in inefficient evaluation of the full kernel.\n",
      "  warnings.warn(\"n_components > n_samples. This is not possible.\\n\"\n",
      "You are already timing task: index_run25\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:59:13,146:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[INFO] [2016-08-16 07:59:13,207:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 270. configuration. Duration: 0.614878; loss: 0.856557; status 1; additional run info: ;duration: 0.6148781776428223;num_run:00270 \n",
      "[INFO] [2016-08-16 07:59:13,215:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 271. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:13,217:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[ERROR] [2016-08-16 07:59:13,248:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:59:13,351:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:59:13,402:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:59:13,887:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 271. configuration. Duration: 0.617685; loss: 0.647541; status 1; additional run info: ;duration: 0.6176848411560059;num_run:00271 \n",
      "[INFO] [2016-08-16 07:59:13,896:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 272. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:13,897:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: libsvm_svc\n",
      "  classifier:libsvm_svc:C, Value: 731.150713256\n",
      "  classifier:libsvm_svc:coef0, Value: 0.467738961408\n",
      "  classifier:libsvm_svc:gamma, Value: 0.00161197537947\n",
      "  classifier:libsvm_svc:kernel, Value: sigmoid\n",
      "  classifier:libsvm_svc:max_iter, Constant: -1\n",
      "  classifier:libsvm_svc:shrinking, Value: False\n",
      "  classifier:libsvm_svc:tol, Value: 0.0159182615907\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 68.0766027974\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/svm/base.py:547: ChangedBehaviorWarning: The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC.\n",
      "  \"SVC.\", ChangedBehaviorWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:59:14,005:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 272. configuration. Duration: 0.071030; loss: 0.860656; status 1; additional run info: ;duration: 0.0710303783416748;num_run:00272 \n",
      "[INFO] [2016-08-16 07:59:14,013:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 273. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:14,016:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:14,711:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 273. configuration. Duration: 0.637126; loss: 0.647541; status 1; additional run info: ;duration: 0.6371257305145264;num_run:00273 \n",
      "[INFO] [2016-08-16 07:59:14,719:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 274. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:14,721:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: sgd\n",
      "  classifier:sgd:alpha, Value: 4.01516225312e-06\n",
      "  classifier:sgd:average, Value: False\n",
      "  classifier:sgd:eta0, Value: 0.045490815558\n",
      "  classifier:sgd:fit_intercept, Constant: True\n",
      "  classifier:sgd:learning_rate, Value: constant\n",
      "  classifier:sgd:loss, Value: perceptron\n",
      "  classifier:sgd:n_iter, Value: 7\n",
      "  classifier:sgd:penalty, Value: l1\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: pca\n",
      "  preprocessor:pca:keep_variance, Value: 0.947414482652\n",
      "  preprocessor:pca:whiten, Value: True\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:59:14,796:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 274. configuration. Duration: 0.033135; loss: 0.901639; status 1; additional run info: ;duration: 0.033135175704956055;num_run:00274 \n",
      "[INFO] [2016-08-16 07:59:14,803:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 275. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:14,805:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:15,578:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 275. configuration. Duration: 0.711133; loss: 0.647541; status 1; additional run info: ;duration: 0.7111327648162842;num_run:00275 \n",
      "[INFO] [2016-08-16 07:59:15,587:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 276. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:15,592:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 3.76314683551\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 2\n",
      "  classifier:random_forest:min_samples_split, Value: 7\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:kernel, Value: cosine\n",
      "  preprocessor:kernel_pca:n_components, Value: 26\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:15,725:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.368852 11: 0.368852 12: 0.372951 13: 0.372951 14: 0.372951 15: 0.368852 16: 0.368852 17: 0.368852 18: 0.368852 19: 0.368852 20: 0.368852 21: 0.368852 22: 0.368852 23: 0.368852 24: 0.368852 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.368852 32: 0.368852 33: 0.368852 34: 0.368852 35: 0.368852 36: 0.368852 37: 0.368852 38: 0.368852 39: 0.368852 40: 0.368852 41: 0.368852 42: 0.368852 43: 0.368852 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.368852 48: 0.368852 49: 0.368852\n",
      "\tMembers: [5, 0, 0, 5, 0, 5, 23, 5, 0, 0, 0, 1, 0, 0, 3, 0, 0, 0, 3, 0, 37, 0, 0, 3, 0, 5, 0, 0, 0, 0, 1, 0, 0, 0, 5, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 5]\n",
      "\tWeights: [ 0.66  0.04  0.    0.12  0.    0.14  0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 40) (1, 67) (1, 71) (1, 79) (1, 149) (1, 211)\n",
      "[INFO] [2016-08-16 07:59:15,759:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.368852\n",
      "[INFO] [2016-08-16 07:59:15,766:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.629172 seconds\n",
      "[INFO] [2016-08-16 07:59:15,775:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (255)!.\n",
      "[INFO] [2016-08-16 07:59:15,782:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (255)!\n",
      "[ERROR] [2016-08-16 07:59:15,808:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:59:15,925:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:59:16,068:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:59:16,131:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:59:16,984:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 276. configuration. Duration: 1.260863; loss: 0.737705; status 1; additional run info: ;duration: 1.2608625888824463;num_run:00276 \n",
      "[INFO] [2016-08-16 07:59:16,993:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 277. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:16,995:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.012740490995\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:17,778:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 277. configuration. Duration: 0.718196; loss: 0.647541; status 1; additional run info: ;duration: 0.718195915222168;num_run:00277 \n",
      "[INFO] [2016-08-16 07:59:17,788:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 278. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:17,790:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: extra_trees\n",
      "  classifier:extra_trees:bootstrap, Value: False\n",
      "  classifier:extra_trees:criterion, Value: entropy\n",
      "  classifier:extra_trees:max_depth, Constant: None\n",
      "  classifier:extra_trees:max_features, Value: 4.34171265251\n",
      "  classifier:extra_trees:min_samples_leaf, Value: 11\n",
      "  classifier:extra_trees:min_samples_split, Value: 14\n",
      "  classifier:extra_trees:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:extra_trees:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0022976889269\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: True\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 2.98063057031\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 16\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 3\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:59:18,308:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 278. configuration. Duration: 0.457024; loss: 0.684426; status 1; additional run info: ;duration: 0.45702409744262695;num_run:00278 \n",
      "[INFO] [2016-08-16 07:59:18,318:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 279. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:18,319:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:18,684:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.368852 11: 0.368852 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.368852 16: 0.368852 17: 0.368852 18: 0.368852 19: 0.372951 20: 0.368852 21: 0.368852 22: 0.372951 23: 0.368852 24: 0.368852 25: 0.372951 26: 0.368852 27: 0.368852 28: 0.372951 29: 0.368852 30: 0.368852 31: 0.372951 32: 0.368852 33: 0.368852 34: 0.372951 35: 0.368852 36: 0.368852 37: 0.368852 38: 0.368852 39: 0.372951 40: 0.368852 41: 0.372951 42: 0.372951 43: 0.368852 44: 0.372951 45: 0.372951 46: 0.368852 47: 0.368852 48: 0.372951 49: 0.368852\n",
      "\tMembers: [3, 0, 0, 3, 0, 3, 20, 3, 0, 0, 0, 3, 0, 0, 3, 0, 0, 0, 3, 0, 0, 3, 0, 0, 3, 0, 0, 3, 0, 0, 3, 0, 0, 3, 0, 3, 0, 0, 3, 20, 0, 3, 0, 0, 3, 0, 0, 0, 3, 0]\n",
      "\tWeights: [ 0.62  0.    0.    0.34  0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.04  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 40) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:59:18,693:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.368852\n",
      "[INFO] [2016-08-16 07:59:18,696:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.897388 seconds\n",
      "[INFO] [2016-08-16 07:59:18,700:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (261)!.\n",
      "[INFO] [2016-08-16 07:59:18,703:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (261)!\n",
      "[ERROR] [2016-08-16 07:59:18,718:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:59:18,799:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:59:18,922:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:59:18,982:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[INFO] [2016-08-16 07:59:19,102:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 279. configuration. Duration: 0.718289; loss: 0.647541; status 1; additional run info: ;duration: 0.7182888984680176;num_run:00279 \n",
      "[INFO] [2016-08-16 07:59:19,111:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 280. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:19,114:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: entropy\n",
      "  classifier:decision_tree:max_depth, Value: 1.13200263385\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 10\n",
      "  classifier:decision_tree:min_samples_split, Value: 11\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: True\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: gini\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 0.768794206873\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 11\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 10\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:59:19,403:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 280. configuration. Duration: 0.236581; loss: 0.659836; status 1; additional run info: ;duration: 0.23658084869384766;num_run:00280 \n",
      "[INFO] [2016-08-16 07:59:19,413:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 281. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:19,416:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:20,198:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 281. configuration. Duration: 0.718480; loss: 0.647541; status 1; additional run info: ;duration: 0.7184803485870361;num_run:00281 \n",
      "[INFO] [2016-08-16 07:59:20,208:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 282. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:20,210:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: gini\n",
      "  classifier:decision_tree:max_depth, Value: 0.0977208800612\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 1\n",
      "  classifier:decision_tree:min_samples_split, Value: 10\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0464557352021\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: extra_trees_preproc_for_classification\n",
      "  preprocessor:extra_trees_preproc_for_classification:bootstrap, Value: True\n",
      "  preprocessor:extra_trees_preproc_for_classification:criterion, Value: entropy\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_depth, Constant: None\n",
      "  preprocessor:extra_trees_preproc_for_classification:max_features, Value: 4.24066599335\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_leaf, Value: 9\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_samples_split, Value: 5\n",
      "  preprocessor:extra_trees_preproc_for_classification:min_weight_fraction_leaf, Constant: 0.0\n",
      "  preprocessor:extra_trees_preproc_for_classification:n_estimators, Constant: 100\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:59:20,516:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 282. configuration. Duration: 0.253466; loss: 1.032787; status 1; additional run info: ;duration: 0.2534658908843994;num_run:00282 \n",
      "[INFO] [2016-08-16 07:59:20,526:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 283. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:20,529:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:21,305:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 283. configuration. Duration: 0.712936; loss: 0.647541; status 1; additional run info: ;duration: 0.7129359245300293;num_run:00283 \n",
      "[INFO] [2016-08-16 07:59:21,314:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 284. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:21,316:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 138\n",
      "  classifier:lda:shrinkage, Value: None\n",
      "  classifier:lda:tol, Value: 0.0221718766779\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0148630536496\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: deflation\n",
      "  preprocessor:fast_ica:fun, Value: logcosh\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:59:21,517:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.368852 2: 0.364754 3: 0.368852 4: 0.368852 5: 0.368852 6: 0.372951 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.368852 11: 0.368852 12: 0.368852 13: 0.368852 14: 0.368852 15: 0.368852 16: 0.368852 17: 0.368852 18: 0.368852 19: 0.372951 20: 0.368852 21: 0.368852 22: 0.372951 23: 0.368852 24: 0.368852 25: 0.372951 26: 0.368852 27: 0.368852 28: 0.372951 29: 0.368852 30: 0.368852 31: 0.372951 32: 0.368852 33: 0.368852 34: 0.372951 35: 0.368852 36: 0.368852 37: 0.368852 38: 0.368852 39: 0.372951 40: 0.368852 41: 0.372951 42: 0.372951 43: 0.368852 44: 0.372951 45: 0.372951 46: 0.368852 47: 0.368852 48: 0.372951 49: 0.368852\n",
      "\tMembers: [3, 0, 0, 3, 0, 3, 20, 3, 0, 0, 0, 3, 0, 0, 3, 0, 0, 0, 3, 0, 0, 3, 0, 0, 3, 0, 0, 3, 0, 0, 3, 0, 0, 3, 0, 3, 0, 0, 3, 20, 0, 3, 0, 0, 3, 0, 0, 0, 3, 0]\n",
      "\tWeights: [ 0.62  0.    0.    0.34  0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.04  0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 40) (1, 79) (1, 149)\n",
      "[INFO] [2016-08-16 07:59:21,525:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.368852\n",
      "[INFO] [2016-08-16 07:59:21,528:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.815318 seconds\n",
      "[INFO] [2016-08-16 07:59:21,530:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:59:22,783:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 284. configuration. Duration: 1.426649; loss: 0.725410; status 1; additional run info: ;duration: 1.4266493320465088;num_run:00284 \n",
      "[INFO] [2016-08-16 07:59:22,792:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 285. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:22,795:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:23,531:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 285. configuration. Duration: 0.677448; loss: 0.647541; status 1; additional run info: ;duration: 0.6774475574493408;num_run:00285 \n",
      "[INFO] [2016-08-16 07:59:23,540:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 286. configuration (from SMAC) with time limit 360s.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run27\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:59:23,542:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: passive_aggressive\n",
      "  classifier:passive_aggressive:C, Value: 0.771761127786\n",
      "  classifier:passive_aggressive:fit_intercept, Constant: True\n",
      "  classifier:passive_aggressive:loss, Value: squared_hinge\n",
      "  classifier:passive_aggressive:n_iter, Value: 891\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[ERROR] [2016-08-16 07:59:23,549:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:59:23,624:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:59:23,736:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:59:23,792:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[ERROR] [2016-08-16 07:59:23,848:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00282.npy has score: -0.0327868852459\n",
      "[INFO] [2016-08-16 07:59:24,506:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 286. configuration. Duration: 0.927629; loss: 0.774590; status 1; additional run info: ;duration: 0.9276289939880371;num_run:00286 \n",
      "[INFO] [2016-08-16 07:59:24,515:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 287. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:24,516:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.202887549518\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 2\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 18\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 274\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.184788347556\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:24,773:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 287. configuration. Duration: 0.218101; loss: 0.684426; status 1; additional run info: ;duration: 0.21810078620910645;num_run:00287 \n",
      "[INFO] [2016-08-16 07:59:24,783:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 288. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:24,784:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gaussian_nb\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00055320016553\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:59:24,857:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 288. configuration. Duration: 0.035266; loss: 0.885246; status 1; additional run info: ;duration: 0.03526639938354492;num_run:00288 \n",
      "[INFO] [2016-08-16 07:59:24,865:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 289. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:24,866:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 4.09855757803\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 5\n",
      "  classifier:random_forest:min_samples_split, Value: 2\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: manhattan\n",
      "  preprocessor:feature_agglomeration:linkage, Value: average\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 168\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: median\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:59:25,172:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 289. configuration. Duration: 0.258311; loss: 0.680328; status 1; additional run info: ;duration: 0.25831103324890137;num_run:00289 \n",
      "[INFO] [2016-08-16 07:59:25,182:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 290. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:25,183:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: False\n",
      "  classifier:random_forest:criterion, Value: gini\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 2.27904317663\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 19\n",
      "  classifier:random_forest:min_samples_split, Value: 10\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:25,573:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 290. configuration. Duration: 0.341999; loss: 0.663934; status 1; additional run info: ;duration: 0.3419992923736572;num_run:00290 \n",
      "[INFO] [2016-08-16 07:59:25,582:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 291. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:25,585:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: liblinear_svc\n",
      "  classifier:liblinear_svc:C, Value: 0.0410131273069\n",
      "  classifier:liblinear_svc:dual, Constant: False\n",
      "  classifier:liblinear_svc:fit_intercept, Constant: True\n",
      "  classifier:liblinear_svc:intercept_scaling, Constant: 1\n",
      "  classifier:liblinear_svc:loss, Value: squared_hinge\n",
      "  classifier:liblinear_svc:multi_class, Constant: ovr\n",
      "  classifier:liblinear_svc:penalty, Value: l2\n",
      "  classifier:liblinear_svc:tol, Value: 0.0515621199664\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:59:25,646:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 291. configuration. Duration: 0.023308; loss: 0.815574; status 1; additional run info: ;duration: 0.02330756187438965;num_run:00291 \n",
      "[INFO] [2016-08-16 07:59:25,654:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 292. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:25,655:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0425186750571\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 5\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 20\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 104\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.412491208946\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0278282782885\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kernel_pca\n",
      "  preprocessor:kernel_pca:coef0, Value: -0.0333107781191\n",
      "  preprocessor:kernel_pca:degree, Value: 3\n",
      "  preprocessor:kernel_pca:gamma, Value: 3.85533308175\n",
      "  preprocessor:kernel_pca:kernel, Value: poly\n",
      "  preprocessor:kernel_pca:n_components, Value: 850\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:26,272:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.356557 2: 0.372951 3: 0.360656 4: 0.360656 5: 0.372951 6: 0.364754 7: 0.364754 8: 0.372951 9: 0.364754 10: 0.368852 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.372951 15: 0.368852 16: 0.368852 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.377049 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.368852 32: 0.368852 33: 0.372951 34: 0.368852 35: 0.368852 36: 0.368852 37: 0.372951 38: 0.368852 39: 0.372951 40: 0.372951 41: 0.368852 42: 0.372951 43: 0.372951 44: 0.368852 45: 0.368852 46: 0.372951 47: 0.368852 48: 0.372951 49: 0.372951\n",
      "\tMembers: [1, 46, 0, 1, 46, 0, 1, 46, 0, 0, 46, 0, 0, 46, 1, 0, 46, 1, 1, 46, 0, 0, 46, 0, 0, 46, 1, 0, 46, 0, 0, 0, 46, 1, 0, 0, 46, 16, 46, 0, 0, 1, 46, 0, 0, 46, 0, 1, 46, 0]\n",
      "\tWeights: [ 0.46  0.2   0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.32  0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 71) (1, 79) (1, 143) (1, 280)\n",
      "[INFO] [2016-08-16 07:59:26,280:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:59:26,282:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.739142 seconds\n",
      "[INFO] [2016-08-16 07:59:26,286:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (271)!.\n",
      "[INFO] [2016-08-16 07:59:26,288:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (271)!\n",
      "[ERROR] [2016-08-16 07:59:26,302:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:59:26,378:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:59:26,493:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:59:26,549:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[ERROR] [2016-08-16 07:59:26,606:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00282.npy has score: -0.0327868852459\n",
      "[INFO] [2016-08-16 07:59:28,901:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.356557 2: 0.372951 3: 0.360656 4: 0.360656 5: 0.372951 6: 0.364754 7: 0.364754 8: 0.372951 9: 0.364754 10: 0.368852 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.372951 15: 0.368852 16: 0.368852 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.377049 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.368852 32: 0.368852 33: 0.372951 34: 0.368852 35: 0.368852 36: 0.368852 37: 0.372951 38: 0.368852 39: 0.372951 40: 0.372951 41: 0.368852 42: 0.372951 43: 0.372951 44: 0.368852 45: 0.368852 46: 0.372951 47: 0.368852 48: 0.372951 49: 0.372951\n",
      "\tMembers: [1, 46, 0, 1, 46, 0, 1, 46, 0, 0, 46, 0, 0, 46, 1, 0, 46, 1, 1, 46, 0, 0, 46, 0, 0, 46, 1, 0, 46, 0, 0, 0, 46, 1, 0, 0, 46, 16, 46, 0, 0, 1, 46, 0, 0, 46, 0, 1, 46, 0]\n",
      "\tWeights: [ 0.46  0.2   0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.32  0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 71) (1, 79) (1, 143) (1, 280)\n",
      "[INFO] [2016-08-16 07:59:28,907:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:59:28,910:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.612866 seconds\n",
      "[INFO] [2016-08-16 07:59:28,912:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:59:31,441:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 292. configuration. Duration: 5.716160; loss: 0.688525; status 1; additional run info: ;duration: 5.71616005897522;num_run:00292 \n",
      "[INFO] [2016-08-16 07:59:32,052:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 236 training points for SMAC.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run28\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:59:32,939:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:59:33,011:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:59:33,122:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:59:33,174:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[ERROR] [2016-08-16 07:59:33,229:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00282.npy has score: -0.0327868852459\n",
      "[INFO] [2016-08-16 07:59:35,380:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.356557 2: 0.372951 3: 0.360656 4: 0.360656 5: 0.372951 6: 0.364754 7: 0.364754 8: 0.372951 9: 0.364754 10: 0.368852 11: 0.372951 12: 0.368852 13: 0.368852 14: 0.372951 15: 0.368852 16: 0.368852 17: 0.372951 18: 0.372951 19: 0.372951 20: 0.372951 21: 0.372951 22: 0.377049 23: 0.372951 24: 0.372951 25: 0.372951 26: 0.372951 27: 0.372951 28: 0.372951 29: 0.372951 30: 0.372951 31: 0.368852 32: 0.368852 33: 0.372951 34: 0.368852 35: 0.368852 36: 0.368852 37: 0.372951 38: 0.368852 39: 0.372951 40: 0.372951 41: 0.368852 42: 0.372951 43: 0.372951 44: 0.368852 45: 0.368852 46: 0.372951 47: 0.368852 48: 0.372951 49: 0.372951\n",
      "\tMembers: [1, 46, 0, 1, 46, 0, 1, 46, 0, 0, 46, 0, 0, 46, 1, 0, 46, 1, 1, 46, 0, 0, 46, 0, 0, 46, 1, 0, 46, 0, 0, 0, 46, 1, 0, 0, 46, 16, 46, 0, 0, 1, 46, 0, 0, 46, 0, 1, 46, 0]\n",
      "\tWeights: [ 0.46  0.2   0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.02  0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.32  0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 71) (1, 79) (1, 143) (1, 280)\n",
      "[INFO] [2016-08-16 07:59:35,387:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:59:35,388:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.454352 seconds\n",
      "[INFO] [2016-08-16 07:59:35,390:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:59:47,352:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 15.2981 seconds to find next configurations\n",
      "[INFO] [2016-08-16 07:59:47,358:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 293. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:47,360:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:47,939:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 293. configuration. Duration: 0.529970; loss: 0.647541; status 1; additional run info: ;duration: 0.5299701690673828;num_run:00293 \n",
      "[INFO] [2016-08-16 07:59:47,947:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 294. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:47,948:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: liblinear_svc\n",
      "  classifier:liblinear_svc:C, Value: 1997.81172408\n",
      "  classifier:liblinear_svc:dual, Constant: False\n",
      "  classifier:liblinear_svc:fit_intercept, Constant: True\n",
      "  classifier:liblinear_svc:intercept_scaling, Constant: 1\n",
      "  classifier:liblinear_svc:loss, Value: squared_hinge\n",
      "  classifier:liblinear_svc:multi_class, Constant: ovr\n",
      "  classifier:liblinear_svc:penalty, Value: l2\n",
      "  classifier:liblinear_svc:tol, Value: 0.00277116924811\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.0215353123495\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/utils/class_weight.py:62: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n",
      "  \" 0.19\", DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:59:48,029:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 294. configuration. Duration: 0.047231; loss: 0.684426; status 1; additional run info: ;duration: 0.047231435775756836;num_run:00294 \n",
      "[INFO] [2016-08-16 07:59:48,036:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 295. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:48,037:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:48,612:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 295. configuration. Duration: 0.525492; loss: 0.647541; status 1; additional run info: ;duration: 0.5254919528961182;num_run:00295 \n",
      "[INFO] [2016-08-16 07:59:48,618:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 296. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:48,619:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.0237053925316\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 7\n",
      "  classifier:gradient_boosting:max_features, Value: 2.2088132815\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 17\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 6\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 120\n",
      "  classifier:gradient_boosting:subsample, Value: 0.584900307831\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: cube\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run28\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:59:49,460:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:59:49,519:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:59:49,611:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:59:49,655:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[ERROR] [2016-08-16 07:59:49,703:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00282.npy has score: -0.0327868852459\n",
      "[INFO] [2016-08-16 07:59:49,958:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 296. configuration. Duration: 1.286519; loss: 0.733607; status 1; additional run info: ;duration: 1.2865190505981445;num_run:00296 \n",
      "[INFO] [2016-08-16 07:59:49,964:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 297. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:49,965:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:50,550:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 297. configuration. Duration: 0.532373; loss: 0.647541; status 1; additional run info: ;duration: 0.5323727130889893;num_run:00297 \n",
      "[INFO] [2016-08-16 07:59:50,557:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 298. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:50,558:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: random_forest\n",
      "  classifier:random_forest:bootstrap, Value: True\n",
      "  classifier:random_forest:criterion, Value: entropy\n",
      "  classifier:random_forest:max_depth, Constant: None\n",
      "  classifier:random_forest:max_features, Value: 2.54828115647\n",
      "  classifier:random_forest:max_leaf_nodes, Constant: None\n",
      "  classifier:random_forest:min_samples_leaf, Value: 10\n",
      "  classifier:random_forest:min_samples_split, Value: 12\n",
      "  classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:random_forest:n_estimators, Constant: 100\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: random_trees_embedding\n",
      "  preprocessor:random_trees_embedding:max_depth, Value: 3\n",
      "  preprocessor:random_trees_embedding:max_leaf_nodes, Constant: None\n",
      "  preprocessor:random_trees_embedding:min_samples_leaf, Value: 12\n",
      "  preprocessor:random_trees_embedding:min_samples_split, Value: 9\n",
      "  preprocessor:random_trees_embedding:min_weight_fraction_leaf, Constant: 1.0\n",
      "  preprocessor:random_trees_embedding:n_estimators, Value: 42\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:59:50,935:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 298. configuration. Duration: 0.336071; loss: 0.692623; status 1; additional run info: ;duration: 0.3360710144042969;num_run:00298 \n",
      "[INFO] [2016-08-16 07:59:50,941:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 299. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:50,943:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000488045939212\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:51,531:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 299. configuration. Duration: 0.537658; loss: 0.647541; status 1; additional run info: ;duration: 0.5376579761505127;num_run:00299 \n",
      "[INFO] [2016-08-16 07:59:51,538:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 300. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:51,540:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: adaboost\n",
      "  classifier:adaboost:algorithm, Value: SAMME\n",
      "  classifier:adaboost:learning_rate, Value: 0.102109207021\n",
      "  classifier:adaboost:max_depth, Value: 1\n",
      "  classifier:adaboost:n_estimators, Value: 119\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: True\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:59:51,552:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.356557 2: 0.372951 3: 0.364754 4: 0.368852 5: 0.364754 6: 0.360656 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.368852 11: 0.364754 12: 0.368852 13: 0.364754 14: 0.368852 15: 0.368852 16: 0.368852 17: 0.364754 18: 0.364754 19: 0.368852 20: 0.368852 21: 0.368852 22: 0.364754 23: 0.364754 24: 0.364754 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.364754 30: 0.368852 31: 0.368852 32: 0.368852 33: 0.368852 34: 0.368852 35: 0.368852 36: 0.368852 37: 0.368852 38: 0.368852 39: 0.368852 40: 0.368852 41: 0.364754 42: 0.364754 43: 0.368852 44: 0.372951 45: 0.372951 46: 0.372951 47: 0.372951 48: 0.372951 49: 0.372951\n",
      "\tMembers: [0, 44, 0, 14, 0, 0, 0, 0, 12, 44, 0, 0, 44, 0, 14, 0, 44, 0, 0, 12, 0, 0, 0, 0, 0, 44, 0, 0, 0, 0, 44, 0, 0, 0, 0, 44, 0, 0, 0, 0, 0, 0, 44, 12, 12, 0, 0, 44, 0, 0]\n",
      "\tWeights: [ 0.7   0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.08  0.    0.04  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.18  0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 79) (1, 121) (1, 143) (1, 280)\n",
      "[INFO] [2016-08-16 07:59:51,558:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:59:51,559:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.104016 seconds\n",
      "[INFO] [2016-08-16 07:59:51,562:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (281)!.\n",
      "[INFO] [2016-08-16 07:59:51,564:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (281)!\n",
      "[ERROR] [2016-08-16 07:59:51,576:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:59:51,638:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:59:51,733:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:59:51,779:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[ERROR] [2016-08-16 07:59:51,827:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00282.npy has score: -0.0327868852459\n",
      "[INFO] [2016-08-16 07:59:53,277:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 300. configuration. Duration: 1.695969; loss: 0.717213; status 1; additional run info: ;duration: 1.6959686279296875;num_run:00300 \n",
      "[INFO] [2016-08-16 07:59:53,284:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 301. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:53,286:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 07:59:53,773:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.356557 2: 0.372951 3: 0.364754 4: 0.368852 5: 0.364754 6: 0.360656 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.360656 11: 0.360656 12: 0.360656 13: 0.360656 14: 0.364754 15: 0.368852 16: 0.368852 17: 0.368852 18: 0.368852 19: 0.368852 20: 0.364754 21: 0.364754 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.368852 32: 0.368852 33: 0.368852 34: 0.368852 35: 0.368852 36: 0.368852 37: 0.368852 38: 0.368852 39: 0.372951 40: 0.372951 41: 0.368852 42: 0.368852 43: 0.368852 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.368852 48: 0.368852 49: 0.372951\n",
      "\tMembers: [0, 42, 0, 12, 0, 0, 0, 0, 12, 12, 0, 22, 0, 0, 42, 0, 0, 0, 0, 12, 12, 12, 42, 12, 12, 0, 0, 0, 0, 0, 42, 0, 0, 0, 0, 0, 0, 0, 0, 12, 12, 0, 42, 0, 0, 0, 0, 0, 0, 12]\n",
      "\tWeights: [ 0.66  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.22  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.1   0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 79) (1, 143) (1, 201) (1, 280)\n",
      "[INFO] [2016-08-16 07:59:53,779:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:59:53,780:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.209031 seconds\n",
      "[INFO] [2016-08-16 07:59:53,783:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (285)!.\n",
      "[INFO] [2016-08-16 07:59:53,785:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (285)!\n",
      "[ERROR] [2016-08-16 07:59:53,798:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:59:53,863:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[INFO] [2016-08-16 07:59:53,911:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 301. configuration. Duration: 0.573492; loss: 0.647541; status 1; additional run info: ;duration: 0.5734922885894775;num_run:00301 \n",
      "[INFO] [2016-08-16 07:59:53,918:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 302. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:53,919:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: decision_tree\n",
      "  classifier:decision_tree:criterion, Value: entropy\n",
      "  classifier:decision_tree:max_depth, Value: 1.37534990148\n",
      "  classifier:decision_tree:max_features, Constant: 1.0\n",
      "  classifier:decision_tree:max_leaf_nodes, Constant: None\n",
      "  classifier:decision_tree:min_samples_leaf, Value: 14\n",
      "  classifier:decision_tree:min_samples_split, Value: 8\n",
      "  classifier:decision_tree:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:decision_tree:splitter, Constant: best\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: fast_ica\n",
      "  preprocessor:fast_ica:algorithm, Value: parallel\n",
      "  preprocessor:fast_ica:fun, Value: exp\n",
      "  preprocessor:fast_ica:whiten, Value: False\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[ERROR] [2016-08-16 07:59:53,963:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[INFO] [2016-08-16 07:59:53,996:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 302. configuration. Duration: 0.034682; loss: 0.790984; status 1; additional run info: ;duration: 0.034682273864746094;num_run:00302 \n",
      "[INFO] [2016-08-16 07:59:54,003:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 303. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:54,004:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[ERROR] [2016-08-16 07:59:54,017:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[ERROR] [2016-08-16 07:59:54,069:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00282.npy has score: -0.0327868852459\n",
      "[INFO] [2016-08-16 07:59:54,642:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 303. configuration. Duration: 0.583653; loss: 0.647541; status 1; additional run info: ;duration: 0.5836532115936279;num_run:00303 \n",
      "[INFO] [2016-08-16 07:59:54,650:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 304. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:54,651:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: qda\n",
      "  classifier:qda:reg_param, Value: 3.56600128576\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 3\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: True\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/discriminant_analysis.py:688: UserWarning: Variables are collinear\n",
      "  warnings.warn(\"Variables are collinear\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 07:59:54,781:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 304. configuration. Duration: 0.086689; loss: 0.897541; status 1; additional run info: ;duration: 0.08668947219848633;num_run:00304 \n",
      "[INFO] [2016-08-16 07:59:54,788:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 305. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:54,790:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.0631532365365\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 4\n",
      "  classifier:gradient_boosting:max_features, Value: 0.993410685749\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 12\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 12\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 161\n",
      "  classifier:gradient_boosting:subsample, Value: 0.833832719862\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00291788854971\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n",
      "[INFO] [2016-08-16 07:59:56,135:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.356557 2: 0.372951 3: 0.364754 4: 0.368852 5: 0.364754 6: 0.360656 7: 0.368852 8: 0.368852 9: 0.368852 10: 0.360656 11: 0.360656 12: 0.360656 13: 0.360656 14: 0.364754 15: 0.368852 16: 0.368852 17: 0.368852 18: 0.368852 19: 0.368852 20: 0.364754 21: 0.364754 22: 0.372951 23: 0.372951 24: 0.372951 25: 0.368852 26: 0.368852 27: 0.368852 28: 0.368852 29: 0.368852 30: 0.368852 31: 0.368852 32: 0.368852 33: 0.368852 34: 0.368852 35: 0.368852 36: 0.368852 37: 0.368852 38: 0.368852 39: 0.372951 40: 0.372951 41: 0.368852 42: 0.368852 43: 0.368852 44: 0.368852 45: 0.368852 46: 0.368852 47: 0.368852 48: 0.368852 49: 0.372951\n",
      "\tMembers: [0, 42, 0, 12, 0, 0, 0, 0, 12, 12, 0, 22, 0, 0, 42, 0, 0, 0, 0, 12, 12, 12, 42, 12, 12, 0, 0, 0, 0, 0, 42, 0, 0, 0, 0, 0, 0, 0, 0, 12, 12, 0, 42, 0, 0, 0, 0, 0, 0, 12]\n",
      "\tWeights: [ 0.66  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.22  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.02  0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.1   0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 79) (1, 143) (1, 201) (1, 280)\n",
      "[INFO] [2016-08-16 07:59:56,143:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.372951\n",
      "[INFO] [2016-08-16 07:59:56,146:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.353026 seconds\n",
      "[INFO] [2016-08-16 07:59:56,149:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 07:59:56,436:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 305. configuration. Duration: 1.581735; loss: 0.754098; status 1; additional run info: ;duration: 1.5817346572875977;num_run:00305 \n",
      "[INFO] [2016-08-16 07:59:56,445:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 306. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:56,446:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.0951052247959\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 4\n",
      "  classifier:gradient_boosting:max_features, Value: 4.22846539056\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 5\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 115\n",
      "  classifier:gradient_boosting:subsample, Value: 0.623087650485\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00404065871665\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: polynomial\n",
      "  preprocessor:polynomial:degree, Value: 2\n",
      "  preprocessor:polynomial:include_bias, Value: False\n",
      "  preprocessor:polynomial:interaction_only, Value: False\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n",
      "[INFO] [2016-08-16 07:59:57,940:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 306. configuration. Duration: 1.435555; loss: 0.713115; status 1; additional run info: ;duration: 1.4355554580688477;num_run:00306 \n",
      "[INFO] [2016-08-16 07:59:57,947:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 307. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:57,950:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: xgradient_boosting\n",
      "  classifier:xgradient_boosting:base_score, Constant: 0.5\n",
      "  classifier:xgradient_boosting:colsample_bylevel, Constant: 1\n",
      "  classifier:xgradient_boosting:colsample_bytree, Constant: 1\n",
      "  classifier:xgradient_boosting:gamma, Constant: 0\n",
      "  classifier:xgradient_boosting:learning_rate, Value: 0.0802082120484\n",
      "  classifier:xgradient_boosting:max_delta_step, Constant: 0\n",
      "  classifier:xgradient_boosting:max_depth, Value: 7\n",
      "  classifier:xgradient_boosting:min_child_weight, Value: 6\n",
      "  classifier:xgradient_boosting:n_estimators, Value: 451\n",
      "  classifier:xgradient_boosting:reg_alpha, Constant: 0\n",
      "  classifier:xgradient_boosting:reg_lambda, Constant: 1\n",
      "  classifier:xgradient_boosting:scale_pos_weight, Constant: 1\n",
      "  classifier:xgradient_boosting:subsample, Value: 0.590333685403\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run30\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 07:59:58,168:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 07:59:58,236:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 07:59:58,339:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 07:59:58,390:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[ERROR] [2016-08-16 07:59:58,442:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00282.npy has score: -0.0327868852459\n",
      "[INFO] [2016-08-16 07:59:59,024:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 307. configuration. Duration: 1.034702; loss: 0.688525; status 1; additional run info: ;duration: 1.0347023010253906;num_run:00307 \n",
      "[INFO] [2016-08-16 07:59:59,033:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 308. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:59,036:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: lda\n",
      "  classifier:lda:n_components, Value: 20\n",
      "  classifier:lda:shrinkage, Value: None\n",
      "  classifier:lda:tol, Value: 8.50556476578e-05\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 0.450958682306\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 149\n",
      "  rescaling:__choice__, Value: min/max\n",
      "\n",
      "[INFO] [2016-08-16 07:59:59,214:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 308. configuration. Duration: 0.106694; loss: 0.754098; status 1; additional run info: ;duration: 0.10669422149658203;num_run:00308 \n",
      "[INFO] [2016-08-16 07:59:59,222:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 309. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 07:59:59,224:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.0123406250819\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.27680648272\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 7\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 17\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 212\n",
      "  classifier:gradient_boosting:subsample, Value: 0.270972072129\n",
      "  imputation:strategy, Value: mean\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.000500473185773\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: feature_agglomeration\n",
      "  preprocessor:feature_agglomeration:affinity, Value: manhattan\n",
      "  preprocessor:feature_agglomeration:linkage, Value: complete\n",
      "  preprocessor:feature_agglomeration:n_clusters, Value: 131\n",
      "  preprocessor:feature_agglomeration:pooling_func, Value: max\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 08:00:00,548:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.352459 2: 0.352459 3: 0.352459 4: 0.352459 5: 0.352459 6: 0.352459 7: 0.352459 8: 0.352459 9: 0.352459 10: 0.352459 11: 0.352459 12: 0.352459 13: 0.352459 14: 0.352459 15: 0.352459 16: 0.352459 17: 0.352459 18: 0.356557 19: 0.356557 20: 0.356557 21: 0.356557 22: 0.360656 23: 0.360656 24: 0.360656 25: 0.360656 26: 0.360656 27: 0.356557 28: 0.356557 29: 0.356557 30: 0.356557 31: 0.356557 32: 0.356557 33: 0.356557 34: 0.356557 35: 0.356557 36: 0.356557 37: 0.356557 38: 0.356557 39: 0.356557 40: 0.356557 41: 0.356557 42: 0.356557 43: 0.356557 44: 0.360656 45: 0.360656 46: 0.360656 47: 0.360656 48: 0.360656 49: 0.360656\n",
      "\tMembers: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.96  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.04  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 79) (1, 143)\n",
      "[INFO] [2016-08-16 08:00:00,556:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.360656\n",
      "[INFO] [2016-08-16 08:00:00,559:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.395845 seconds\n",
      "[INFO] [2016-08-16 08:00:00,563:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many validation set predictions (0)as ensemble predictions (292)!.\n",
      "[INFO] [2016-08-16 08:00:00,564:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Could not find as many test set predictions (0) as ensemble predictions (292)!\n",
      "[ERROR] [2016-08-16 08:00:00,577:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 08:00:00,647:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 08:00:00,751:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 08:00:00,803:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[ERROR] [2016-08-16 08:00:00,856:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00282.npy has score: -0.0327868852459\n",
      "[INFO] [2016-08-16 08:00:01,267:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 309. configuration. Duration: 1.971730; loss: 0.668033; status 1; additional run info: ;duration: 1.9717304706573486;num_run:00309 \n",
      "[INFO] [2016-08-16 08:00:01,275:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 310. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 08:00:01,277:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: qda\n",
      "  classifier:qda:reg_param, Value: 2.91906564205\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00038327831332\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: kitchen_sinks\n",
      "  preprocessor:kitchen_sinks:gamma, Value: 0.661046144339\n",
      "  preprocessor:kitchen_sinks:n_components, Value: 9993\n",
      "  rescaling:__choice__, Value: standardize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/sklearn/discriminant_analysis.py:688: UserWarning: Variables are collinear\n",
      "  warnings.warn(\"Variables are collinear\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] [2016-08-16 08:00:04,298:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.352459 2: 0.352459 3: 0.352459 4: 0.352459 5: 0.352459 6: 0.352459 7: 0.352459 8: 0.352459 9: 0.352459 10: 0.352459 11: 0.352459 12: 0.352459 13: 0.352459 14: 0.352459 15: 0.352459 16: 0.352459 17: 0.352459 18: 0.356557 19: 0.356557 20: 0.356557 21: 0.356557 22: 0.360656 23: 0.360656 24: 0.360656 25: 0.360656 26: 0.360656 27: 0.356557 28: 0.356557 29: 0.356557 30: 0.356557 31: 0.356557 32: 0.356557 33: 0.356557 34: 0.356557 35: 0.356557 36: 0.356557 37: 0.356557 38: 0.356557 39: 0.356557 40: 0.356557 41: 0.356557 42: 0.356557 43: 0.356557 44: 0.360656 45: 0.360656 46: 0.360656 47: 0.360656 48: 0.360656 49: 0.360656\n",
      "\tMembers: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.96  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.04  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 79) (1, 143)\n",
      "[INFO] [2016-08-16 08:00:04,319:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.360656\n",
      "[INFO] [2016-08-16 08:00:04,324:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 3.751712 seconds\n",
      "[INFO] [2016-08-16 08:00:04,329:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 08:00:05,134:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 310. configuration. Duration: 3.684906; loss: 0.909836; status 1; additional run info: ;duration: 3.684906005859375;num_run:00310 \n",
      "[INFO] [2016-08-16 08:00:05,889:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Using 249 training points for SMAC.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run31\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 08:00:06,355:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 08:00:06,441:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 08:00:06,571:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00176.npy has score: -0.159836065574\n",
      "[ERROR] [2016-08-16 08:00:06,634:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00228.npy has score: -0.016393442623\n",
      "[ERROR] [2016-08-16 08:00:06,700:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00282.npy has score: -0.0327868852459\n",
      "[INFO] [2016-08-16 08:00:09,326:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble Selection:\n",
      "\tTrajectory: 0: 0.352459 1: 0.352459 2: 0.352459 3: 0.352459 4: 0.352459 5: 0.352459 6: 0.352459 7: 0.352459 8: 0.352459 9: 0.352459 10: 0.352459 11: 0.352459 12: 0.352459 13: 0.352459 14: 0.352459 15: 0.352459 16: 0.352459 17: 0.352459 18: 0.356557 19: 0.356557 20: 0.356557 21: 0.356557 22: 0.360656 23: 0.360656 24: 0.360656 25: 0.360656 26: 0.360656 27: 0.356557 28: 0.356557 29: 0.356557 30: 0.356557 31: 0.356557 32: 0.356557 33: 0.356557 34: 0.356557 35: 0.356557 36: 0.356557 37: 0.356557 38: 0.356557 39: 0.356557 40: 0.356557 41: 0.356557 42: 0.356557 43: 0.356557 44: 0.360656 45: 0.360656 46: 0.360656 47: 0.360656 48: 0.360656 49: 0.360656\n",
      "\tMembers: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0]\n",
      "\tWeights: [ 0.96  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.04  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.\n",
      "  0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.  ]\n",
      "\tIdentifiers: (1, 79) (1, 143)\n",
      "[INFO] [2016-08-16 08:00:09,333:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Training performance: 0.360656\n",
      "[INFO] [2016-08-16 08:00:09,335:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Building the ensemble took 2.986415 seconds\n",
      "[INFO] [2016-08-16 08:00:09,337:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Ensemble output did not change.\n",
      "[INFO] [2016-08-16 08:00:18,565:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Used 12.6745 seconds to find next configurations\n",
      "[INFO] [2016-08-16 08:00:18,571:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 311. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 08:00:18,573:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: none\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.1\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 3\n",
      "  classifier:gradient_boosting:max_features, Value: 1.0\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 1\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 2\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 100\n",
      "  classifier:gradient_boosting:subsample, Value: 1.0\n",
      "  imputation:strategy, Value: median\n",
      "  one_hot_encoding:minimum_fraction, Value: 0.00382888292142\n",
      "  one_hot_encoding:use_minimum_fraction, Value: True\n",
      "  preprocessor:__choice__, Value: no_preprocessing\n",
      "  rescaling:__choice__, Value: none\n",
      "\n",
      "[INFO] [2016-08-16 08:00:19,155:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Finished evaluating 311. configuration. Duration: 0.532541; loss: 0.647541; status 1; additional run info: ;duration: 0.5325412750244141;num_run:00311 \n",
      "[INFO] [2016-08-16 08:00:19,163:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Starting to evaluate 312. configuration (from SMAC) with time limit 360s.\n",
      "[INFO] [2016-08-16 08:00:19,165:AutoMLSMBO(1)::7a3a10b65f5366b76f046add6da72a1c] Configuration:\n",
      "  balancing:strategy, Value: weighting\n",
      "  classifier:__choice__, Value: gradient_boosting\n",
      "  classifier:gradient_boosting:learning_rate, Value: 0.0110206252034\n",
      "  classifier:gradient_boosting:loss, Constant: deviance\n",
      "  classifier:gradient_boosting:max_depth, Value: 8\n",
      "  classifier:gradient_boosting:max_features, Value: 3.01751308323\n",
      "  classifier:gradient_boosting:max_leaf_nodes, Constant: None\n",
      "  classifier:gradient_boosting:min_samples_leaf, Value: 12\n",
      "  classifier:gradient_boosting:min_samples_split, Value: 20\n",
      "  classifier:gradient_boosting:min_weight_fraction_leaf, Constant: 0.0\n",
      "  classifier:gradient_boosting:n_estimators, Value: 391\n",
      "  classifier:gradient_boosting:subsample, Value: 0.960310296709\n",
      "  imputation:strategy, Value: most_frequent\n",
      "  one_hot_encoding:use_minimum_fraction, Value: False\n",
      "  preprocessor:__choice__, Value: select_percentile_classification\n",
      "  preprocessor:select_percentile_classification:percentile, Value: 24.4276507313\n",
      "  preprocessor:select_percentile_classification:score_func, Value: chi2\n",
      "  rescaling:__choice__, Value: normalize\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are already timing task: index_run31\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ERROR] [2016-08-16 08:00:19,392:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00005.npy has score: -0.0983606557377\n",
      "[ERROR] [2016-08-16 08:00:19,452:EnsembleBuilder(1):7a3a10b65f5366b76f046add6da72a1c] Model only predicts at random: /tmp/autosklearn_tmp_676_7642/.auto-sklearn/predictions_ensemble/predictions_ensemble_1_00074.npy has score: -0.0737704918033\n",
      "[ERROR] [2016-08-16 08:00:19,542:EnsembleBuilder(1):7a

# Fixed code
def fit(
    self,
    X,
    y,
    task=MULTICLASS_CLASSIFICATION,
    metric="acc_metric",
    feat_type=None,
    dataset_name=None,
):
    if not self._shared_mode:
        self._backend.context.delete_directories()
    else:
        # If this fails, it's likely that this is the first call to get
        # the data manager
        try:
            D = self._backend.load_datamanager()
            dataset_name = D.name
        except IOError:
            pass

    self._backend.context.create_directories()

    if dataset_name is None:
        dataset_name = hash_numpy_array(X)

    self._backend.save_start_time(self._seed)
    self._stopwatch = StopWatch()
    self._dataset_name = dataset_name
    self._stopwatch.start_task(self._dataset_name)

    self._logger = self._get_logger(dataset_name)

    if isinstance(metric, str):
        metric = STRING_TO_METRIC[metric]

    if feat_type is not None and len(feat_type) != X.shape[1]:
        raise ValueError(
            "Array feat_type does not have same number of "
            "variables as X has features. %d vs %d." % (len(feat_type), X.shape[1])
        )
    if feat_type is not None and not all([isinstance(f, str) for f in feat_type]):
        raise ValueError("Array feat_type must only contain strings.")
    if feat_type is not None:
        for ft in feat_type:
            if ft.lower() not in ["categorical", "numerical"]:
                raise ValueError(
                    "Only `Categorical` and `Numerical` are "
                    "valid feature types, you passed `%s`" % ft
                )

    self._data_memory_limit = None
    loaded_data_manager = XYDataManager(
        X,
        y,
        task=task,
        metric=metric,
        feat_type=feat_type,
        dataset_name=dataset_name,
        encode_labels=False,
    )

    return self._fit(loaded_data_manager)