{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>BP</th>\n",
       "      <th>Cholesterol</th>\n",
       "      <th>Na_to_K</th>\n",
       "      <th>Drug</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>48</td>\n",
       "      <td>M</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>NORMAL</td>\n",
       "      <td>10.446</td>\n",
       "      <td>drugA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>61</td>\n",
       "      <td>F</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>25.475</td>\n",
       "      <td>DrugY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>68</td>\n",
       "      <td>F</td>\n",
       "      <td>NORMAL</td>\n",
       "      <td>NORMAL</td>\n",
       "      <td>27.050</td>\n",
       "      <td>DrugY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age Sex      BP Cholesterol  Na_to_K   Drug\n",
       "176   48   M    HIGH      NORMAL   10.446  drugA\n",
       "119   61   F    HIGH        HIGH   25.475  DrugY\n",
       "65    68   F  NORMAL      NORMAL   27.050  DrugY"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "drug_df = pd.read_csv(\"Data/drug.csv\")\n",
    "drug_df = drug_df.sample(frac=1)\n",
    "drug_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X = drug_df.drop(\"Drug\", axis=1).values\n",
    "y = drug_df.Drug.values\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, test_size=0.3, random_state=125\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;,\n",
       "                 ColumnTransformer(transformers=[(&#x27;encoder&#x27;, OrdinalEncoder(),\n",
       "                                                  [1, 2, 3]),\n",
       "                                                 (&#x27;num_imputer&#x27;,\n",
       "                                                  SimpleImputer(strategy=&#x27;median&#x27;),\n",
       "                                                  [0, 4]),\n",
       "                                                 (&#x27;num_scaler&#x27;,\n",
       "                                                  StandardScaler(), [0, 4])])),\n",
       "                (&#x27;model&#x27;,\n",
       "                 RandomForestClassifier(n_estimators=10, random_state=125))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;,\n",
       "                 ColumnTransformer(transformers=[(&#x27;encoder&#x27;, OrdinalEncoder(),\n",
       "                                                  [1, 2, 3]),\n",
       "                                                 (&#x27;num_imputer&#x27;,\n",
       "                                                  SimpleImputer(strategy=&#x27;median&#x27;),\n",
       "                                                  [0, 4]),\n",
       "                                                 (&#x27;num_scaler&#x27;,\n",
       "                                                  StandardScaler(), [0, 4])])),\n",
       "                (&#x27;model&#x27;,\n",
       "                 RandomForestClassifier(n_estimators=10, random_state=125))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;preprocessing: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for preprocessing: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(transformers=[(&#x27;encoder&#x27;, OrdinalEncoder(), [1, 2, 3]),\n",
       "                                (&#x27;num_imputer&#x27;,\n",
       "                                 SimpleImputer(strategy=&#x27;median&#x27;), [0, 4]),\n",
       "                                (&#x27;num_scaler&#x27;, StandardScaler(), [0, 4])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">encoder</label><div class=\"sk-toggleable__content fitted\"><pre>[1, 2, 3]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OrdinalEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.OrdinalEncoder.html\">?<span>Documentation for OrdinalEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OrdinalEncoder()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">num_imputer</label><div class=\"sk-toggleable__content fitted\"><pre>[0, 4]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;SimpleImputer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.impute.SimpleImputer.html\">?<span>Documentation for SimpleImputer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>SimpleImputer(strategy=&#x27;median&#x27;)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">num_scaler</label><div class=\"sk-toggleable__content fitted\"><pre>[0, 4]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;RandomForestClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier(n_estimators=10, random_state=125)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('preprocessing',\n",
       "                 ColumnTransformer(transformers=[('encoder', OrdinalEncoder(),\n",
       "                                                  [1, 2, 3]),\n",
       "                                                 ('num_imputer',\n",
       "                                                  SimpleImputer(strategy='median'),\n",
       "                                                  [0, 4]),\n",
       "                                                 ('num_scaler',\n",
       "                                                  StandardScaler(), [0, 4])])),\n",
       "                ('model',\n",
       "                 RandomForestClassifier(n_estimators=10, random_state=125))])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import OrdinalEncoder, StandardScaler\n",
    "\n",
    "cat_col = [1,2,3]\n",
    "num_col = [0,4]\n",
    "\n",
    "transform = ColumnTransformer(\n",
    "    [\n",
    "        (\"encoder\", OrdinalEncoder(), cat_col),\n",
    "        (\"num_imputer\", SimpleImputer(strategy=\"median\"), num_col),\n",
    "        (\"num_scaler\", StandardScaler(), num_col),\n",
    "    ]\n",
    ")\n",
    "pipe = Pipeline(\n",
    "    steps=[\n",
    "        (\"preprocessing\", transform),\n",
    "        (\"model\", RandomForestClassifier(n_estimators=10, random_state=125)),\n",
    "    ]\n",
    ")\n",
    "pipe.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy:  90.0% F1:  0.85\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score, f1_score\n",
    "\n",
    "predictions = pipe.predict(X_test)\n",
    "accuracy = accuracy_score(y_test, predictions)\n",
    "f1 = f1_score(y_test, predictions, average=\"macro\")\n",
    "\n",
    "print(\"Accuracy: \", str(round(accuracy, 2) * 100) + \"%\", \"F1: \", round(f1, 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write metrics to file\n",
    "with open(\"Results/metrics.txt\", \"w\") as outfile:\n",
    "    outfile.write(f\"\\nAccuracy = {round(accuracy,2)}, F1 Score = {round(f1,2)}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import ConfusionMatrixDisplay, confusion_matrix\n",
    "\n",
    "predictions = pipe.predict(X_test)\n",
    "cm = confusion_matrix(y_test, predictions, labels=pipe.classes_)\n",
    "disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=pipe.classes_)\n",
    "disp.plot()\n",
    "plt.savefig(\"Results/model_results.png\", dpi=120)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import skops.io as sio\n",
    "\n",
    "sio.dump(pipe, \"Model/drug_pipeline.skops\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;,\n",
       "                 ColumnTransformer(transformers=[(&#x27;encoder&#x27;, OrdinalEncoder(),\n",
       "                                                  [1, 2, 3]),\n",
       "                                                 (&#x27;num_imputer&#x27;,\n",
       "                                                  SimpleImputer(strategy=&#x27;median&#x27;),\n",
       "                                                  [0, 4]),\n",
       "                                                 (&#x27;num_scaler&#x27;,\n",
       "                                                  StandardScaler(), [0, 4])])),\n",
       "                (&#x27;model&#x27;,\n",
       "                 RandomForestClassifier(n_estimators=10, random_state=125))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;,\n",
       "                 ColumnTransformer(transformers=[(&#x27;encoder&#x27;, OrdinalEncoder(),\n",
       "                                                  [1, 2, 3]),\n",
       "                                                 (&#x27;num_imputer&#x27;,\n",
       "                                                  SimpleImputer(strategy=&#x27;median&#x27;),\n",
       "                                                  [0, 4]),\n",
       "                                                 (&#x27;num_scaler&#x27;,\n",
       "                                                  StandardScaler(), [0, 4])])),\n",
       "                (&#x27;model&#x27;,\n",
       "                 RandomForestClassifier(n_estimators=10, random_state=125))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-11\" type=\"checkbox\" ><label for=\"sk-estimator-id-11\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;preprocessing: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for preprocessing: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(transformers=[(&#x27;encoder&#x27;, OrdinalEncoder(), [1, 2, 3]),\n",
       "                                (&#x27;num_imputer&#x27;,\n",
       "                                 SimpleImputer(strategy=&#x27;median&#x27;), [0, 4]),\n",
       "                                (&#x27;num_scaler&#x27;, StandardScaler(), [0, 4])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-12\" type=\"checkbox\" ><label for=\"sk-estimator-id-12\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">encoder</label><div class=\"sk-toggleable__content fitted\"><pre>[1, 2, 3]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-13\" type=\"checkbox\" ><label for=\"sk-estimator-id-13\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OrdinalEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.OrdinalEncoder.html\">?<span>Documentation for OrdinalEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OrdinalEncoder()</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-14\" type=\"checkbox\" ><label for=\"sk-estimator-id-14\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">num_imputer</label><div class=\"sk-toggleable__content fitted\"><pre>[0, 4]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-15\" type=\"checkbox\" ><label for=\"sk-estimator-id-15\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;SimpleImputer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.impute.SimpleImputer.html\">?<span>Documentation for SimpleImputer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>SimpleImputer(strategy=&#x27;median&#x27;)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-16\" type=\"checkbox\" ><label for=\"sk-estimator-id-16\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">num_scaler</label><div class=\"sk-toggleable__content fitted\"><pre>[0, 4]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-17\" type=\"checkbox\" ><label for=\"sk-estimator-id-17\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-18\" type=\"checkbox\" ><label for=\"sk-estimator-id-18\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;RandomForestClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier(n_estimators=10, random_state=125)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('preprocessing',\n",
       "                 ColumnTransformer(transformers=[('encoder', OrdinalEncoder(),\n",
       "                                                  [1, 2, 3]),\n",
       "                                                 ('num_imputer',\n",
       "                                                  SimpleImputer(strategy='median'),\n",
       "                                                  [0, 4]),\n",
       "                                                 ('num_scaler',\n",
       "                                                  StandardScaler(), [0, 4])])),\n",
       "                ('model',\n",
       "                 RandomForestClassifier(n_estimators=10, random_state=125))])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sio.load(\"Model/drug_pipeline.skops\", trusted=True)"
   ]
  }
 ],
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