Kaggle competition: Natural Language Processing with Disaster Tweets
<SOS> metric: meanfscore Kaggle data source: natural-language-processing-with-disaster-tweets<define_search_space>
!curl https://raw.githubusercontent.com/pytorch/xla/master/contrib/scripts/env-setup.py -o pytorch-xla-env-setup.py > /dev/null
!python pytorch-xla-env-setup.py --version 20200420 --apt-packages libomp5 libopenblas-dev > /dev/null
!pip install transformers==2.5.1 > /dev/null
!pip install pandarallel > /dev/null
!pip install catalyst==20.4.2 > /dev/null
<train_model>
os.environ['XLA_USE_BF16'] = "1"
tqdm.pandas()
nltk.download('punkt')
 pandarallel.initialize(nb_workers=4, progress_bar=False )
def runXGB(xtrain,xvalid,ytrain,yvalid,xtest,eta=0.07,num_rounds=100,max_depth=8):
params = {
'objective':'binary:logistic',
'max_depth':max_depth,
'learning_rate':eta,
'eval_metric':'auc',
'min_child_weight':6,
'subsample':0.8,
'colsample_bytree':0.8,
'seed':seed,
'reg_lambda':1.3,
'reg_alpha':8,
'gamma':10,
'scale_pos_weight':1.6,
'nthread':-1
}
dtrain = xgb.DMatrix(xtrain,label=ytrain)
 dvalid = xgb.DMatrix(xvalid,label=yvalid)
 dtest = xgb.DMatrix(xtest)
 watchlist = [(dtrain,'train'),(dvalid,'test')]
model = xgb.train(params,dtrain,num_rounds,watchlist,early_stopping_rounds=300,verbose_eval=20)
 pred = model.predict(dvalid,ntree_limit=model.best_ntree_limit)
 pred_test = model.predict(dtest,ntree_limit=model.best_ntree_limit)
 return pred_test,model 
<split>
SEED = 42
MAX_LENGTH = 64
BACKBONE_PATH = 'roberta-base'
ROOT_PATH = f'.. '
def seed_everything(seed):
random.seed(seed)
 os.environ['PYTHONHASHSEED'] = str(seed)
 np.random.seed(seed)
 torch.manual_seed(seed)
 torch.cuda.manual_seed(seed)
 torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = True
seed_everything(SEED )
kf = StratifiedKFold(n_splits=5,random_state=seed,shuffle=True)
 pred_test_full =0
cv_score = []
i=1
for train_index,test_index in kf.split(X,y):
print('{} of KFold {}'.format(i,kf.n_splits))
xtr,xvl = X.loc[train_index],X.loc[test_index]
ytr,yvl = y[train_index],y[test_index]
pred_test,xg_model = runXGB(xtr,xvl,ytr,yvl,x_test,num_rounds=500,eta=0.1)
 pred_test_full += pred_test
cv_score.append(xg_model.best_score)
 i+=1<compute_test_metric>
def get_sentences(text):
sentences = sent_tokenize(text)
 return ' '.join(sentences)
 def clean_text(text):
text = str(text)
 text = re.sub(r'[0-9"]', '', text)
 text = re.sub(r'
text = re.sub(r'@[\S]+\b', '', text)
 text = re.sub(r'https?\S+', '', text)
 text = re.sub(r'\s+', ' ', text)
 text = get_sentences(text)
 return text.strip()
class NLPTransform(BasicTransform):

 @property
def targets(self):
return {"data": self.apply}
def update_params(self, params, **kwargs):
if hasattr(self, "interpolation"):
params["interpolation"] = self.interpolation
if hasattr(self, "fill_value"):
params["fill_value"] = self.fill_value
return params
def get_sentences(self, text):
return sent_tokenize(text)
 class ShuffleSentencesTransform(NLPTransform):

 def __init__(self, always_apply=False, p=0.5):
super(ShuffleSentencesTransform, self ).__init__(always_apply, p)
 def apply(self, data, **params):
text = data
sentences = self.get_sentences(text)
 random.shuffle(sentences)
 return ' '.join(sentences)
 class ExcludeNumbersTransform(NLPTransform):

 def __init__(self, always_apply=False, p=0.5):
super(ExcludeNumbersTransform, self ).__init__(always_apply, p)
 def apply(self, data, **params):
text = data
text = re.sub(r'[0-9]', '', text)
 text = re.sub(r'\s+', ' ', text)
 return text
class ExcludeHashtagsTransform(NLPTransform):
Exclude @users Exclude urls
print(cv_score)
 print('Mean cv_score',np.mean(cv_score))<define_variables>
def get_train_transforms() :
return albumentations.Compose([
ExcludeUsersMentionedTransform(p=0.95),
ExcludeUrlsTransform(p=0.95),
ExcludeNumbersTransform(p=0.95),
ExcludeHashtagsTransform(p=0.95),
], p=1.0)
 train_transforms = get_train_transforms()
tokenizer = RobertaTokenizer.from_pretrained(BACKBONE_PATH)
 shuffle_transforms = ShuffleSentencesTransform(always_apply=True )
pred_xgb = pred_test_full/kf.n_splits<save_to_csv>
def onehot(size, target):
vec = torch.zeros(size, dtype=torch.float32)
 vec[target] = 1.
 return vec
class DatasetRetriever(Dataset):
def __init__(self, labels_or_ids, texts, use_train_transforms=False, test=False):
self.test = test
self.labels_or_ids = labels_or_ids
self.texts = texts
self.use_train_transforms = use_train_transforms
def get_tokens(self, text):
encoded = tokenizer.encode_plus(
 text,
add_special_tokens=True,
max_length=MAX_LENGTH,
pad_to_max_length=True 
)
 return encoded['input_ids'], encoded['attention_mask']
def __len__(self):
return self.texts.shape[0]
def __getitem__(self, idx):
text = self.texts[idx]
if self.test is False:
label = self.labels_or_ids[idx]
target = onehot(2, label)
 if self.use_train_transforms:
text = train_transforms(data=(text)) ['data']
tokens, attention_mask = self.get_tokens(str(text))
token_length = sum(attention_mask)
 if token_length > 0.8*MAX_LENGTH:
text = shuffle_transforms(data=(text)) ['data']
else:
tokens, attention_mask = torch.tensor(tokens), torch.tensor(attention_mask)
 return target, tokens, attention_mask
tokens, attention_mask = self.get_tokens(str(text))
tokens, attention_mask = torch.tensor(tokens), torch.tensor(attention_mask)
 if self.test is False:
return target, tokens, attention_mask
return self.labels_or_ids[idx], tokens, attention_mask
def get_labels(self):
return list(self.labels_or_ids.astype(str))
y_pred = pred_xgb
submit = pd.DataFrame({'id':test_id,'target':y_pred})
 submit.to_csv('xgb_porto.csv',index=False)
<define_variables>
df = pd.read_csv(f'{ROOT_PATH}/input/nlp-getting-started/train.csv')
 X = df['text'].values
y = df['target'].values
X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.25, random_state=42, stratify=y)
 df_train = pd.DataFrame(
 {'target': y_train,
'text': X_train})
 df_val = pd.DataFrame(
 {'target': y_val,
'text': X_val})
 del df
gc.collect() ;
C_REGULARIZER = 3
N_FOLDS = 5
SHOW_COEFS = False<import_modules>
validation_tune_dataset = DatasetRetriever(
 labels_or_ids=df_val['target'].values,
texts=df_val['text'].values,
use_train_transforms=True, 
)
 df_val['text'] = df_val.apply(lambda x: clean_text(x['text']), axis=1)
 validation_dataset = DatasetRetriever(
 labels_or_ids=df_val['target'].values,
texts=df_val['text'].values,
use_train_transforms=False, 
)
 del df_val
gc.collect() ;
for targets, tokens, attention_masks in validation_dataset:
break
print(targets)
 print(tokens.shape)
 print(attention_masks.shape )
import numpy as np
import pandas as pd
from sklearn.model_selection import StratifiedKFold
from sklearn.model_selection import train_test_split
from sklearn.model_selection import KFold
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import roc_auc_score
from sklearn.linear_model import LogisticRegression
from xgboost import XGBClassifier
import xgboost as xgb
from numba import jit
import gc<compute_test_metric>
df_test = pd.read_csv(f'{ROOT_PATH}/input/nlp-getting-started/test.csv', index_col='id')
 df_test['text'] = df_test.parallel_apply(lambda x: clean_text(x['text']), axis=1)
 test_dataset = DatasetRetriever(
 labels_or_ids=df_test.index.values,
texts=df_test['text'].values,
use_train_transforms=False,
test=True 
)
 del df_test
gc.collect() ;
for ids, tokens, attention_masks in test_dataset:
break
print(ids)
 print(tokens.shape)
 print(attention_masks.shape )
def GiniScore(y_actual, y_pred):
return 2*roc_auc_score(y_actual, y_pred)-1
def Outputs(p):
return 1./(1.+np.exp(-p))<compute_train_metric>
class RocAucMeter(object):
def __init__(self):
self.reset()
def reset(self):
self.y_true = np.array([0,1])
 self.y_pred = np.array([0.5,0.5])
 self.score = 0
def update(self, y_true, y_pred):
y_true = y_true.cpu().numpy().argmax(axis=1)
 y_pred = nn.functional.softmax(y_pred, dim=1 ).data.cpu().numpy() [:,1]
self.y_true = np.hstack(( self.y_true, y_true))
self.y_pred = np.hstack(( self.y_pred, y_pred))
self.score = sklearn.metrics.roc_auc_score(self.y_true, self.y_pred, labels=np.array([0, 1]))
@property
def avg(self):
return self.score
class AverageMeter(object):

 def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum / self.count
@jit
def eval_gini(y_true, y_prob):
y_true = np.asarray(y_true)
 y_true = y_true[np.argsort(y_prob)]
ntrue = 0
gini = 0
delta = 0
n = len(y_true)
 for i in range(n-1, -1, -1):
y_i = y_true[i]
ntrue += y_i
gini += y_i * delta
delta += 1 - y_i
gini = 1 - 2 * gini /(ntrue *(n - ntrue))
return gini<split>
class LabelSmoothing(nn.Module):
def __init__(self, smoothing = 0.1):
super(LabelSmoothing, self ).__init__()
self.confidence = 1.0 - smoothing
self.smoothing = smoothing
def forward(self, x, target):
if self.training:
x = x.float()
target = target.float()
logprobs = torch.nn.functional.log_softmax(x, dim = -1)
 nll_loss = -logprobs * target
nll_loss = nll_loss.sum(-1)
 smooth_loss = -logprobs.mean(dim=-1)
 loss = self.confidence * nll_loss + self.smoothing * smooth_loss
return loss.mean()
else:
return torch.nn.functional.cross_entropy(x, target )
def apply_model(data, test_data, preproc, state):
LR = LogisticRegression(
 C=C_REGULARIZER,
fit_intercept=False 
)
 print('Processing data...')
 K = N_FOLDS
kf = KFold(n_splits = K, random_state = 1, shuffle = True)
 train_df = preproc(data)
 y_valid_pred = 0*data.target
test_df = preproc(test_data)
 y_test = 0
for i,(train_index, test_index)in enumerate(kf.split(data)) :
print('
Fold:',i)
 y, y_val = data.target.iloc[train_index].copy() , data.target.iloc[test_index].copy()
X, X_val = train_df.iloc[train_index,:].copy() , train_df.iloc[test_index,:].copy()
X_test = test_df.copy()
model = LR.fit(X, y)
 del X, y
if SHOW_COEFS:
coefs = pd.Series(data=np.reshape(LR.coef_,-1), index=train_df.columns.values)
 print('Coefficients:', coefs)
 y_pred = model.predict_proba(X_val)[:,1]
print('Gini score: ', eval_gini(y_val, y_pred))
y_valid_pred.iloc[test_index] = y_pred
del X_val, y_val
y_test += model.predict_proba(X_test)[:,1]
y_test /= K
print('Gini score: ', eval_gini(data.target, y_valid_pred))
return(y_valid_pred, y_test)
<statistical_test>
warnings.filterwarnings("ignore")
 class TPUFitter:
def __init__(self, model, device, config):
if not os.path.exists('node_submissions'):
os.makedirs('node_submissions')
 self.config = config
self.epoch = 0
self.log_path = 'log.txt'
self.model = model
self.device = device
param_optimizer = list(self.model.named_parameters())
 no_decay = ['bias', 'LayerNorm.bias', 'LayerNorm.weight']
optimizer_grouped_parameters = [
{'params': [p for n, p in param_optimizer if not any(nd in n for nd in no_decay)], 'weight_decay': 0.001},
{'params': [p for n, p in param_optimizer if any(nd in n for nd in no_decay)], 'weight_decay': 0.0}
]
self.optimizer = AdamW(optimizer_grouped_parameters, lr=config.lr*xm.xrt_world_size())
 self.scheduler = config.SchedulerClass(self.optimizer, **config.scheduler_params)
 self.criterion = config.criterion
xm.master_print(f'Fitter prepared.Device is {self.device}')
 def fit(self, train_loader, validation_loader):
for e in range(self.config.n_epochs):
if self.config.verbose:
lr = self.optimizer.param_groups[0]['lr']
timestamp = datetime.utcnow().isoformat()
self.log(f'
{timestamp}
LR: {lr}')
 t = time.time()
para_loader = pl.ParallelLoader(train_loader, [self.device])
 losses, final_scores = self.train_one_epoch(para_loader.per_device_loader(self.device))
self.log(f'[RESULT]: Train.Epoch: {self.epoch}, loss: {losses.avg:.5f}, final_score: {final_scores.avg:.5f}, time: {(time.time() - t):.5f}')
 t = time.time()
para_loader = pl.ParallelLoader(validation_loader, [self.device])
 losses, final_scores = self.validation(para_loader.per_device_loader(self.device))
self.log(f'[RESULT]: Validation.Epoch: {self.epoch}, loss: {losses.avg:.5f}, final_score: {final_scores.avg:.5f}, time: {(time.time() - t):.5f}')
 if self.config.validation_scheduler:
self.scheduler.step(metrics=final_scores.avg)
 self.epoch += 1
def run_tuning_and_inference(self, test_loader, validation_tune_loader):
for e in range(2):
self.optimizer.param_groups[0]['lr'] = self.config.lr*xm.xrt_world_size()
para_loader = pl.ParallelLoader(validation_tune_loader, [self.device])
 losses, final_scores = self.train_one_epoch(para_loader.per_device_loader(self.device))
para_loader = pl.ParallelLoader(test_loader, [self.device])
 self.run_inference(para_loader.per_device_loader(self.device))
def validation(self, val_loader):
self.model.eval()
losses = AverageMeter()
final_scores = RocAucMeter()
t = time.time()
for step,(targets, inputs, attention_masks)in enumerate(val_loader):
if self.config.verbose:
if step % self.config.verbose_step == 0:
xm.master_print(
 f'Valid Step {step}, loss: ' + \
f'{losses.avg:.5f}, final_score: {final_scores.avg:.5f}, ' + \
f'time: {(time.time() - t):.5f}' 
)
 with torch.no_grad() :
inputs = inputs.to(self.device, dtype=torch.long)
 attention_masks = attention_masks.to(self.device, dtype=torch.long)
 targets = targets.to(self.device, dtype=torch.float)
 outputs = self.model(inputs, attention_masks)
 loss = self.criterion(outputs, targets)
 batch_size = inputs.size(0)
 final_scores.update(targets, outputs)
 losses.update(loss.detach().item() , batch_size)
 return losses, final_scores
def train_one_epoch(self, train_loader):
self.model.train()
losses = AverageMeter()
final_scores = RocAucMeter()
t = time.time()
for step,(targets, inputs, attention_masks)in enumerate(train_loader):
if self.config.verbose:
if step % self.config.verbose_step == 0:
self.log(
 f'Train Step {step}, loss: ' + \
f'{losses.avg:.5f}, final_score: {final_scores.avg:.5f}, ' + \
f'time: {(time.time() - t):.5f}' 
)
 inputs = inputs.to(self.device, dtype=torch.long)
 attention_masks = attention_masks.to(self.device, dtype=torch.long)
 targets = targets.to(self.device, dtype=torch.float)
 self.optimizer.zero_grad()
outputs = self.model(inputs, attention_masks)
 loss = self.criterion(outputs, targets)
 batch_size = inputs.size(0)
 final_scores.update(targets, outputs)
 losses.update(loss.detach().item() , batch_size)
 loss.backward()
xm.optimizer_step(self.optimizer)
 if self.config.step_scheduler:
self.scheduler.step()
self.model.eval()
self.save('last-checkpoint.bin')
 return losses, final_scores
def run_inference(self, test_loader):
self.model.eval()
result = {'id': [], 'target': []}
t = time.time()
for step,(ids, inputs, attention_masks)in enumerate(test_loader):
if self.config.verbose:
if step % self.config.verbose_step == 0:
xm.master_print(f'Prediction Step {step}, time: {(time.time() - t):.5f}')
 with torch.no_grad() :
inputs = inputs.to(self.device, dtype=torch.long)
 attention_masks = attention_masks.to(self.device, dtype=torch.long)
 outputs = self.model(inputs, attention_masks)
 toxics = nn.functional.softmax(outputs, dim=1 ).data.cpu().numpy() [:,1]
result['id'].extend(ids.cpu().numpy())
 result['target'].extend(toxics)
 result = pd.DataFrame(result)
 node_count = len(glob('node_submissions/*.csv'))
result.to_csv(f'node_submissions/submission_{node_count}_{datetime.utcnow().microsecond}_{random.random() }.csv', index=False)
 def save(self, path):
xm.save(self.model.state_dict() , path)
 def log(self, message):
if self.config.verbose:
xm.master_print(message)
 with open(self.log_path, 'a+')as logger:
xm.master_print(f'{message}', logger )
def GPI(data):
v = get_GP1_features(data)
 return Outputs(v.sum(axis=1))
def GPII(data):
v = get_GP2_features(data)
 return Outputs(v.sum(axis=1))<feature_engineering>
class NNModel(nn.Module):
def __init__(self):
super(NNModel, self ).__init__()
self.backbone = RobertaModel.from_pretrained(BACKBONE_PATH)
 self.dropout = nn.Dropout(0.3)
 self.linear = nn.Linear(
 in_features=self.backbone.pooler.dense.out_features*2,
out_features=2, 
)
 def forward(self, input_ids, attention_masks):
bs, seq_length = input_ids.shape
seq_x, _ = self.backbone(input_ids=input_ids, attention_mask=attention_masks)
 apool = torch.mean(seq_x, 1)
 mpool, _ = torch.max(seq_x, 1)
 x = torch.cat(( apool, mpool), 1)
 x = self.dropout(x)
 return self.linear(x )
def get_GP1_features(data):
v = pd.DataFrame()
v["1"] = 0.020000*np.tanh(( data["loo_ps_ind_06_bin"] +(data["ps_reg_01"] +(data["ps_car_12"] +(data["loo_ps_car_03_cat"] + data["loo_ps_car_07_cat"])))))
 v["2"] = 0.020000*np.tanh(( data["loo_ps_ind_17_bin"] +(( data["ps_reg_03"] + data["ps_car_12"])+(data["loo_ps_ind_06_bin"] + data["loo_ps_ind_05_cat"]))))
v["3"] = 0.020000*np.tanh(( data["loo_ps_car_01_cat"] +(data["loo_ps_ind_17_bin"] +(( data["ps_car_12"] + data["ps_reg_03"])+ data["loo_ps_ind_07_bin"]))))
v["4"] = 0.020000*np.tanh(( data["loo_ps_car_01_cat"] +(( data["loo_ps_car_04_cat"] +(data["ps_reg_03"] + data["ps_car_15"])) * 3.0)))
 v["5"] = 0.020000*np.tanh(((data["ps_car_13"] +(( data["loo_ps_car_05_cat"] +(data["ps_reg_01"] + data["loo_ps_car_09_cat"])) /2.0)) *(10.28825187683105469)))
 v["6"] = 0.020000*np.tanh(((8.0)*(data["loo_ps_car_04_cat"] +(( data["loo_ps_car_01_cat"] + data["loo_ps_ind_05_cat"])+ data["ps_car_15"]))))
v["7"] = 0.020000*np.tanh(((data["ps_car_13"] +(((data["loo_ps_car_01_cat"] + data["ps_reg_03"])+ data["loo_ps_ind_16_bin"])/2.0)) * 8.428570))
v["8"] = 0.020000*np.tanh(((10.86397266387939453)*(((data["ps_reg_03"] + data["loo_ps_car_07_cat"])+ data["loo_ps_ind_06_bin"])+ data["loo_ps_car_11_cat"])))
 v["9"] = 0.020000*np.tanh(( data["ps_reg_03"] +(data["loo_ps_ind_16_bin"] +(data["loo_ps_ind_07_bin"] +(data["ps_car_13"] + data["loo_ps_car_03_cat"])))))
 v["10"] = 0.020000*np.tanh(((( data["ps_car_13"] + data["ps_reg_02"])- data["ps_ind_15"])+(data["loo_ps_car_11_cat"] + data["loo_ps_ind_17_bin"])))
 v["11"] = 0.020000*np.tanh(((data["ps_car_13"] + data["ps_reg_02"])+(data["loo_ps_ind_07_bin"] +(data["loo_ps_ind_17_bin"] + data["loo_ps_car_01_cat"]))))
v["12"] = 0.020000*np.tanh(((data["ps_car_13"] +(data["ps_reg_02"] +(( data["loo_ps_car_09_cat"] + data["loo_ps_ind_16_bin"])/2.0)))* 8.428570))
v["13"] = 0.020000*np.tanh(( data["ps_reg_02"] +(data["loo_ps_ind_08_bin"] +(( data["loo_ps_ind_16_bin"] + data["ps_car_13"])+ data["loo_ps_ind_07_bin"]))))
v["14"] = 0.020000*np.tanh(( 29.500000 *(((data["ps_car_13"] +(data["loo_ps_car_09_cat"] + data["loo_ps_ind_16_bin"])) /2.0)+ data["loo_ps_ind_05_cat"])))
 v["15"] = 0.020000*np.tanh(( 29.500000 *(( data["loo_ps_car_04_cat"] +(data["loo_ps_car_03_cat"] + data["ps_car_13"])) + 0.945455)))
 v["16"] = 0.020000*np.tanh(( 8.428570 *(( data["loo_ps_ind_05_cat"] + data["loo_ps_car_06_cat"])+(data["loo_ps_car_07_cat"] + data["loo_ps_ind_17_bin"]))))
v["17"] = 0.020000*np.tanh(((( 0.633333 +(data["loo_ps_ind_17_bin"] + data["ps_car_13"])) + data["ps_reg_03"])* 29.500000))
v["18"] = 0.020000*np.tanh(((( data["loo_ps_ind_17_bin"] + data["loo_ps_car_11_cat"])+(data["loo_ps_car_07_cat"] - data["ps_ind_15"])) + data["ps_ind_03"]))
v["19"] = 0.020000*np.tanh(((data["loo_ps_car_07_cat"] +(data["loo_ps_ind_05_cat"] +(data["loo_ps_ind_09_bin"] + data["loo_ps_ind_06_bin"])))*(4.85490655899047852)))
 v["20"] = 0.020000*np.tanh(((((data["loo_ps_ind_06_bin"] + data["loo_ps_car_11_cat"])+ data["loo_ps_car_07_cat"])+ data["loo_ps_car_09_cat"])- data["ps_ind_15"]))
v["21"] = 0.020000*np.tanh(( 8.428570 *(( data["loo_ps_ind_05_cat"] + data["ps_car_13"])+(( data["loo_ps_car_05_cat"] + data["loo_ps_car_01_cat"])/2.0))))
v["22"] = 0.020000*np.tanh(((( data["ps_ind_03"] +(data["loo_ps_ind_16_bin"] +(data["loo_ps_ind_05_cat"] + data["loo_ps_ind_06_bin"])))/2.0)* 29.500000))
v["23"] = 0.020000*np.tanh(((data["loo_ps_ind_17_bin"] +(data["loo_ps_ind_09_bin"] +(data["ps_reg_03"] + data["loo_ps_ind_05_cat"])))* 29.500000))
v["24"] = 0.020000*np.tanh(( data["loo_ps_car_03_cat"] -(data["ps_ind_15"] -(data["loo_ps_ind_05_cat"] +(( data["loo_ps_ind_07_bin"] + data["loo_ps_ind_17_bin"])/2.0)))))
 v["25"] = 0.020000*np.tanh(((data["ps_reg_02"] +(( data["loo_ps_car_07_cat"] - -1.0)+ data["ps_car_13"])) *(13.29769420623779297)))
 v["26"] = 0.020000*np.tanh(( 29.500000 *(((( data["loo_ps_car_01_cat"] + data["ps_car_13"])/2.0)+(data["loo_ps_ind_05_cat"] + data["loo_ps_ind_17_bin"])) /2.0)))
 v["27"] = 0.020000*np.tanh(( data["ps_reg_03"] +(1.480000 +(data["loo_ps_ind_06_bin"] +(data["loo_ps_car_11_cat"] + data["loo_ps_car_01_cat"])))))
 v["28"] = 0.020000*np.tanh(( data["loo_ps_car_11_cat"] +(( data["loo_ps_ind_05_cat"] +(data["loo_ps_car_09_cat"] - data["ps_ind_15"])) + data["loo_ps_car_03_cat"])))
 v["29"] = 0.020000*np.tanh(((10.24501132965087891)*(data["loo_ps_ind_05_cat"] +(data["ps_ind_03"] +(data["loo_ps_ind_09_bin"] - data["ps_ind_15"])))))
 v["30"] = 0.020000*np.tanh(((data["loo_ps_car_11_cat"] +(data["loo_ps_ind_05_cat"] + data["loo_ps_car_07_cat"])) +(data["loo_ps_car_09_cat"] - data["missing"])))
 v["31"] = 0.020000*np.tanh(( 29.500000 *(data["loo_ps_car_01_cat"] +(( data["loo_ps_car_07_cat"] + data["loo_ps_ind_05_cat"])+ data["loo_ps_ind_16_bin"]))))
v["32"] = 0.020000*np.tanh(((data["ps_reg_03"] +(( data["ps_ind_01"] + 0.887097)+ data["loo_ps_car_09_cat"])) *(10.0)))
 v["33"] = 0.020000*np.tanh(((data["loo_ps_car_03_cat"] +(data["loo_ps_car_03_cat"] -(data["ps_ind_15"] - 1.480000)))* 29.500000))
v["34"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] +(( 14.32789230346679688)*(data["ps_ind_03"] +(data["ps_ind_03"] * data["ps_ind_03"])))))
 v["35"] = 0.020000*np.tanh(( 29.500000 *(data["loo_ps_ind_17_bin"] +(((data["ps_car_13"] + data["ps_ind_03"])/2.0)+ data["loo_ps_ind_05_cat"]))))
v["36"] = 0.020000*np.tanh(((9.0)*(data["ps_reg_02"] +(data["loo_ps_car_07_cat"] +(( data["ps_car_15"] + 1.0)/2.0)))))
 v["37"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] +(data["loo_ps_ind_08_bin"] +(( data["loo_ps_ind_16_bin"] + data["loo_ps_ind_07_bin"])/2.0)))* 8.428570))
v["38"] = 0.020000*np.tanh(((2.0 *(( data["loo_ps_car_03_cat"] + data["loo_ps_car_07_cat"])+ data["loo_ps_ind_05_cat"])) + data["loo_ps_car_04_cat"]))
v["39"] = 0.020000*np.tanh(( 29.500000 *(data["loo_ps_ind_07_bin"] +(( data["loo_ps_car_07_cat"] + 1.089890)- data["ps_ind_15"]))))
v["40"] = 0.020000*np.tanh(((10.18701076507568359)*(( data["ps_ind_03"] * data["ps_ind_03"])+(data["loo_ps_ind_05_cat"] + data["ps_ind_03"]))))
v["41"] = 0.020000*np.tanh(( 8.428570 *(data["loo_ps_ind_02_cat"] +(data["ps_car_13"] +(data["loo_ps_car_07_cat"] + data["loo_ps_ind_09_bin"])))))
 v["42"] = 0.020000*np.tanh(( 8.428570 *(((data["loo_ps_car_01_cat"] - 0.435484)+ data["loo_ps_ind_05_cat"])+ data["loo_ps_ind_17_bin"])))
 v["43"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] +(29.500000 *(data["ps_ind_03"] +(data["ps_ind_03"] * data["ps_ind_03"])))))
 v["44"] = 0.020000*np.tanh(( 8.428570 *(( data["loo_ps_ind_05_cat"] + data["loo_ps_car_09_cat"])-(data["ps_ind_15"] + data["loo_ps_ind_18_bin"]))))
v["45"] = 0.020000*np.tanh(( data["ps_ind_01"] +(( 5.76565647125244141)*(data["loo_ps_ind_07_bin"] +(0.887097 - data["ps_ind_15"])))))
 v["46"] = 0.020000*np.tanh(((7.0)*(2.352940 *(( data["ps_ind_03"] * data["ps_ind_03"])+ data["ps_ind_03"]))))
v["47"] = 0.020000*np.tanh(( 29.500000 *(( data["loo_ps_ind_17_bin"] +(data["loo_ps_ind_17_bin"] + data["loo_ps_ind_05_cat"])) - data["ps_ind_03"])))
 v["48"] = 0.020000*np.tanh(((9.90538215637207031)*(((data["loo_ps_ind_06_bin"] + data["loo_ps_car_07_cat"])+ data["loo_ps_ind_09_bin"])+ data["loo_ps_ind_09_bin"])))
 v["49"] = 0.020000*np.tanh(( data["ps_ind_01"] +(( data["loo_ps_car_01_cat"] +(data["ps_ind_01"] + data["loo_ps_ind_06_bin"])) + data["loo_ps_car_09_cat"])))
 v["50"] = 0.020000*np.tanh(( 29.500000 *(data["loo_ps_ind_02_cat"] +(data["loo_ps_car_09_cat"] +(( data["loo_ps_car_07_cat"] + data["loo_ps_ind_05_cat"])/2.0)))))
 v["51"] = 0.020000*np.tanh(( 29.500000 *(data["ps_car_13"] +(data["loo_ps_ind_05_cat"] +(data["loo_ps_ind_06_bin"] - 2.352940)))))
 v["52"] = 0.020000*np.tanh(( 29.500000 *(data["loo_ps_ind_04_cat"] +(data["loo_ps_ind_05_cat"] +(data["loo_ps_ind_07_bin"] * data["ps_ind_03"])))))
 v["53"] = 0.020000*np.tanh(( 29.500000 *(((9.0)*(( data["loo_ps_ind_04_cat"] + data["ps_reg_03"])/2.0)) - data["ps_ind_15"])))
 v["54"] = 0.020000*np.tanh(( data["loo_ps_ind_17_bin"] +(data["loo_ps_ind_04_cat"] +(data["loo_ps_ind_17_bin"] +(data["ps_reg_02"] * data["loo_ps_ind_05_cat"])))))
 v["55"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] +(( data["loo_ps_ind_06_bin"] *(data["ps_ind_03"] + data["loo_ps_ind_05_cat"])) - data["ps_car_11"])))
 v["56"] = 0.020000*np.tanh(((data["ps_ind_01"] +(data["ps_ind_03"] + data["loo_ps_ind_05_cat"])) *(data["loo_ps_ind_07_bin"] + data["loo_ps_car_05_cat"])))
 v["57"] = 0.020000*np.tanh(((data["loo_ps_ind_16_bin"] * data["loo_ps_car_03_cat"])-(data["ps_ind_15"] -(( data["ps_reg_02"] + data["loo_ps_ind_02_cat"])/2.0))))
v["58"] = 0.020000*np.tanh(((( data["ps_car_13"] + -2.0)+(data["loo_ps_ind_05_cat"] - data["ps_ind_15"])) - data["ps_car_11"]))
v["59"] = 0.020000*np.tanh(((data["ps_car_15"] +(3.0 * data["loo_ps_ind_17_bin"])) +(data["ps_ind_03"] * data["ps_ind_03"])))
 v["60"] = 0.020000*np.tanh(( 29.500000 *(( data["ps_ind_03"] * data["ps_ind_03"])+ data["ps_ind_03"])))
 v["61"] = 0.020000*np.tanh(((( data["loo_ps_ind_17_bin"] + data["missing"])+(data["loo_ps_car_11_cat"] + data["loo_ps_ind_17_bin"])) * data["loo_ps_car_05_cat"]))
v["62"] = 0.020000*np.tanh(( 8.428570 +(((data["loo_ps_car_03_cat"] * data["loo_ps_ind_09_bin"])+ data["loo_ps_car_01_cat"])* 29.500000)))
 v["63"] = 0.020000*np.tanh(((data["ps_ind_01"] +(data["loo_ps_car_11_cat"] + data["loo_ps_car_05_cat"])) *(data["loo_ps_ind_05_cat"] - data["ps_car_11"])))
 v["64"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] +(data["ps_ind_01"] +(data["loo_ps_ind_09_bin"] *(data["ps_ind_03"] + data["ps_ind_01"])))))
 v["65"] = 0.020000*np.tanh(((data["loo_ps_car_11_cat"] + data["loo_ps_ind_02_cat"])+(data["loo_ps_car_05_cat"] *(data["loo_ps_ind_09_bin"] + data["loo_ps_ind_06_bin"]))))
v["66"] = 0.020000*np.tanh(((( data["loo_ps_ind_05_cat"] * data["loo_ps_ind_06_bin"])* 29.500000)+(data["loo_ps_ind_02_cat"] * data["loo_ps_ind_05_cat"])))
 v["67"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] - data["ps_reg_01"])*(( data["ps_ind_01"] + data["loo_ps_ind_06_bin"])+ data["loo_ps_car_11_cat"])))
 v["68"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] - data["ps_car_11"])*(3.0 *(data["loo_ps_ind_17_bin"] + data["loo_ps_car_04_cat"]))))
v["69"] = 0.019996*np.tanh(((( data["ps_reg_02"] - data["ps_car_11"])+(data["loo_ps_ind_04_cat"] * 3.0)) - data["ps_ind_15"]))
v["70"] = 0.020000*np.tanh(( -(( data["loo_ps_ind_02_cat"] *(data["ps_ind_03"] +(data["ps_ind_03"] + data["ps_ind_03"]))))))
v["71"] = 0.020000*np.tanh(( data["loo_ps_ind_17_bin"] +(data["missing"] +(( 8.37885093688964844)*(data["loo_ps_ind_17_bin"] + data["loo_ps_ind_02_cat"])))))
 v["72"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] +(data["ps_reg_03"] +(1.480000 *(data["loo_ps_car_04_cat"] * data["ps_ind_01"])))))
 v["73"] = 0.020000*np.tanh(((((5.0)* data["loo_ps_ind_05_cat"])+ data["loo_ps_car_09_cat"])*(data["loo_ps_ind_17_bin"] + data["ps_reg_03"])))
 v["74"] = 0.020000*np.tanh(((((data["loo_ps_ind_07_bin"] + data["loo_ps_car_01_cat"])/2.0)* data["loo_ps_ind_16_bin"])+(data["ps_ind_15"] * data["loo_ps_ind_18_bin"])))
 v["75"] = 0.020000*np.tanh(((( data["loo_ps_ind_05_cat"] * data["loo_ps_car_01_cat"])+ data["loo_ps_car_05_cat"])*(data["loo_ps_ind_05_cat"] - data["ps_ind_15"])))
 v["76"] = 0.020000*np.tanh(( data["loo_ps_ind_16_bin"] *(( data["loo_ps_car_04_cat"] + data["loo_ps_ind_05_cat"])+(data["loo_ps_car_07_cat"] + data["ps_ind_03"]))))
v["77"] = 0.020000*np.tanh(((data["loo_ps_car_05_cat"] + data["loo_ps_car_03_cat"])*(data["ps_ind_03"] +(data["missing"] + data["loo_ps_ind_05_cat"]))))
v["78"] = 0.020000*np.tanh(((data["ps_ind_01"] * data["loo_ps_car_03_cat"])+(data["loo_ps_car_08_cat"] +(data["loo_ps_ind_17_bin"] * data["loo_ps_car_03_cat"]))))
v["79"] = 0.020000*np.tanh(( data["ps_ind_03"] *(3.0 *(3.0 *(-(data["loo_ps_ind_02_cat"]))))))
v["80"] = 0.020000*np.tanh(((( data["loo_ps_ind_05_cat"] + data["loo_ps_ind_05_cat"])*(data["loo_ps_car_09_cat"] + data["ps_reg_03"])) - data["loo_ps_ind_16_bin"]))
v["81"] = 0.020000*np.tanh(( data["loo_ps_car_03_cat"] *(( data["loo_ps_ind_09_bin"] - data["ps_car_15"])+(data["loo_ps_ind_02_cat"] - data["loo_ps_ind_18_bin"]))))
v["82"] = 0.020000*np.tanh(((( data["ps_ind_01"] + data["loo_ps_ind_06_bin"])*(data["loo_ps_ind_16_bin"] - data["ps_reg_01"])) + data["loo_ps_car_07_cat"]))
v["83"] = 0.020000*np.tanh(( data["ps_ind_15"] *(data["loo_ps_ind_16_bin"] -(( data["loo_ps_car_11_cat"] + data["missing"])+ data["loo_ps_ind_17_bin"]))))
v["84"] = 0.020000*np.tanh(((( data["loo_ps_ind_07_bin"] + data["loo_ps_ind_02_cat"])/2.0)+(data["ps_ind_01"] *(0.600000 - data["ps_ind_15"]))))
v["85"] = 0.020000*np.tanh(((data["ps_ind_01"] + data["loo_ps_car_04_cat"])*(( data["loo_ps_ind_05_cat"] - data["ps_ind_15"])+ -1.0)))
 v["86"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] +(data["ps_reg_03"] +(data["ps_reg_03"] +(data["loo_ps_ind_17_bin"] * data["loo_ps_car_07_cat"])))))
 v["87"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(((( 4.0)* data["loo_ps_ind_17_bin"])+ data["loo_ps_car_06_cat"])- data["ps_reg_01"])))
 v["88"] = 0.020000*np.tanh(((-1.0 + data["loo_ps_ind_12_bin"])-(data["loo_ps_car_10_cat"] +(data["ps_car_11"] - data["loo_ps_car_09_cat"]))))
v["89"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(( data["loo_ps_car_09_cat"] +(( -1.0 + data["ps_reg_03"])/2.0)) + data["ps_reg_03"])))
 v["90"] = 0.020000*np.tanh(((( data["loo_ps_ind_09_bin"] + data["loo_ps_ind_05_cat"])*(( data["loo_ps_ind_05_cat"] + data["loo_ps_ind_17_bin"])/2.0)) - data["loo_ps_ind_05_cat"]))
v["91"] = 0.020000*np.tanh(( -(((data["loo_ps_ind_02_cat"] + data["loo_ps_ind_02_cat"])*(data["ps_ind_03"] + data["loo_ps_ind_06_bin"])))))
 v["92"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] +(data["ps_reg_03"] *(( -(data["ps_reg_01"])) + data["loo_ps_ind_17_bin"]))))
v["93"] = 0.020000*np.tanh(((data["loo_ps_ind_02_cat"] * 29.500000)*(data["loo_ps_car_08_cat"] +(data["loo_ps_car_08_cat"] - data["ps_ind_03"]))))
v["94"] = 0.020000*np.tanh(((( data["loo_ps_car_03_cat"] * data["loo_ps_car_09_cat"])*(data["loo_ps_car_04_cat"] * data["loo_ps_car_04_cat"])) - data["loo_ps_car_04_cat"]))
v["95"] = 0.020000*np.tanh(((data["loo_ps_car_07_cat"] + -1.0)-(data["ps_car_12"] *(2.0 * data["ps_car_11"]))))
v["96"] = 0.020000*np.tanh(( -(( data["ps_reg_03"] *(( data["loo_ps_car_01_cat"] - data["loo_ps_car_03_cat"])+ data["loo_ps_ind_08_bin"])))))
 v["97"] = 0.020000*np.tanh(( data["loo_ps_ind_16_bin"] *(data["loo_ps_car_07_cat"] +(((data["loo_ps_ind_07_bin"] + data["ps_car_12"])/2.0)- data["ps_reg_01"]))))
v["98"] = 0.020000*np.tanh(((((data["loo_ps_ind_07_bin"] + data["ps_ind_15"])/2.0)+ data["loo_ps_ind_17_bin"])*(data["loo_ps_ind_05_cat"] + data["loo_ps_ind_05_cat"])))
 v["99"] = 0.019992*np.tanh(((data["loo_ps_ind_05_cat"] * data["loo_ps_car_09_cat"])+(-(( data["ps_reg_01"] * data["ps_ind_03"])))))
 v["100"] = 0.019988*np.tanh(( data["loo_ps_ind_04_cat"] +(data["loo_ps_car_05_cat"] *(data["ps_ind_01"] +(data["ps_ind_01"] + data["loo_ps_car_01_cat"])))))
 v["101"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(data["loo_ps_ind_05_cat"] * np.tanh(( data["loo_ps_ind_05_cat"] +(-(2.352940)))))))
 v["102"] = 0.020000*np.tanh(( -(( data["ps_reg_01"] *(data["loo_ps_car_09_cat"] +(data["ps_reg_03"] + data["loo_ps_ind_05_cat"]))))))
v["103"] = 0.020000*np.tanh(((-1.0 +(data["loo_ps_car_09_cat"] +(( data["ps_reg_01"] * data["ps_reg_01"])+ data["ps_reg_01"])))/2.0))
v["104"] = 0.020000*np.tanh(((data["loo_ps_ind_17_bin"] +(( data["loo_ps_ind_02_cat"] + -2.0)/2.0)) *(data["loo_ps_ind_05_cat"] - data["ps_car_15"])))
 v["105"] = 0.019992*np.tanh(((( data["loo_ps_ind_17_bin"] + data["loo_ps_car_07_cat"])+ data["loo_ps_ind_17_bin"])*(( data["ps_reg_02"] + data["loo_ps_car_09_cat"])/2.0)))
 v["106"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(data["loo_ps_ind_07_bin"] +(data["loo_ps_ind_07_bin"] +(data["loo_ps_car_09_cat"] + -1.0)))))
 v["107"] = 0.020000*np.tanh(((data["ps_car_15"] +(data["loo_ps_ind_07_bin"] * data["loo_ps_ind_17_bin"])) -(data["ps_reg_03"] * data["loo_ps_car_01_cat"])))
 v["108"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] *(( data["loo_ps_ind_04_cat"] -(data["loo_ps_ind_06_bin"] - 0.432099)) - data["loo_ps_car_01_cat"])))
 v["109"] = 0.019988*np.tanh(( data["loo_ps_ind_02_cat"] -(data["ps_ind_01"] *(-2.0 +(data["ps_ind_01"] * data["ps_ind_01"])))))
 v["110"] = 0.020000*np.tanh(((29.500000 +(data["ps_car_15"] * 29.500000)) *(0.791667 - data["ps_car_15"])))
 v["111"] = 0.020000*np.tanh(((((data["loo_ps_ind_04_cat"] + -1.0)+ data["loo_ps_car_08_cat"])/2.0)+(data["loo_ps_ind_05_cat"] * data["ps_reg_03"])))
 v["112"] = 0.020000*np.tanh(( data["loo_ps_car_01_cat"] *(( data["ps_reg_03"] *(( data["loo_ps_car_05_cat"] + data["ps_reg_03"])/2.0)) - data["ps_car_15"])))
 v["113"] = 0.020000*np.tanh(( data["ps_reg_02"] *(( data["loo_ps_ind_17_bin"] - data["loo_ps_car_01_cat"])-(data["ps_ind_01"] - data["loo_ps_ind_17_bin"]))))
v["114"] = 0.020000*np.tanh(( data["ps_ind_03"] *(data["ps_reg_03"] -(1.480000 +(data["ps_ind_15"] - data["ps_reg_03"])))))
 v["115"] = 0.019988*np.tanh(((((data["loo_ps_car_01_cat"] +(data["ps_car_11"] * data["ps_car_11"])) /2.0)+(data["ps_reg_01"] * data["missing"])) /2.0))
v["116"] = 0.020000*np.tanh(((data["loo_ps_ind_04_cat"] *(( data["loo_ps_ind_04_cat"] - data["ps_ind_01"])+ data["ps_ind_03"])) - data["loo_ps_ind_02_cat"]))
v["117"] = 0.020000*np.tanh(( data["loo_ps_car_04_cat"] *(( data["loo_ps_car_09_cat"] - data["ps_car_11"])-(( data["loo_ps_car_06_cat"] + data["loo_ps_car_04_cat"])/2.0))))
v["118"] = 0.020000*np.tanh(((( data["loo_ps_ind_04_cat"] + data["ps_ind_03"])/2.0)*(( data["loo_ps_car_02_cat"] - data["ps_reg_01"])+ data["loo_ps_car_07_cat"])))
 v["119"] = 0.020000*np.tanh(((((data["ps_car_15"] *(-(data["loo_ps_car_03_cat"])))+ data["loo_ps_car_01_cat"])/2.0)- data["loo_ps_car_07_cat"]))
v["120"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(( data["loo_ps_ind_05_cat"] *(data["loo_ps_car_03_cat"] * data["loo_ps_car_11_cat"])) - 0.633333)))
 v["121"] = 0.020000*np.tanh(((((data["loo_ps_ind_05_cat"] + data["ps_car_12"])+ data["loo_ps_ind_18_bin"])/2.0)*(( data["missing"] + data["ps_reg_02"])/2.0)))
 v["122"] = 0.020000*np.tanh(((((data["ps_ind_03"] + data["loo_ps_ind_04_cat"])/2.0)*(( data["ps_ind_03"] + data["loo_ps_ind_04_cat"])/2.0)) - 0.432099))
v["123"] = 0.020000*np.tanh(((data["ps_reg_03"] * data["ps_reg_03"])*(((data["loo_ps_ind_05_cat"] - data["ps_reg_03"])+ data["ps_car_12"])/2.0)))
 v["124"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(data["ps_car_13"] +(( data["loo_ps_car_04_cat"] - data["ps_ind_03"])- 1.089890))))
v["125"] = 0.020000*np.tanh(((( data["loo_ps_car_09_cat"] + -2.0)/2.0)*(data["loo_ps_ind_02_cat"] +(data["ps_car_11"] * data["ps_ind_01"]))))
v["126"] = 0.019988*np.tanh(((data["loo_ps_ind_02_cat"] +(( data["loo_ps_car_07_cat"] * data["loo_ps_ind_08_bin"])-(data["ps_ind_15"] * data["loo_ps_car_06_cat"])))/2.0))
v["127"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] *(data["loo_ps_car_09_cat"] * np.tanh(((data["loo_ps_ind_07_bin"] +(-(data["ps_ind_03"])))/2.0)))))
 v["128"] = 0.020000*np.tanh(((( data["missing"] - data["ps_car_11"])*(data["loo_ps_car_01_cat"] - data["loo_ps_car_06_cat"])) - data["loo_ps_car_11_cat"]))
v["129"] = 0.020000*np.tanh(( data["ps_reg_01"] *(-(( np.tanh(( data["ps_reg_03"] + data["loo_ps_ind_05_cat"])) + data["loo_ps_ind_18_bin"])))))
 v["130"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(( data["missing"] + data["ps_car_11"])+ data["ps_ind_15"])))
 v["131"] = 0.019996*np.tanh(((( data["loo_ps_ind_02_cat"] - data["loo_ps_car_04_cat"])+(( data["loo_ps_ind_07_bin"] * data["ps_car_13"])* data["ps_reg_03"])) /2.0))
v["132"] = 0.020000*np.tanh(( data["ps_reg_01"] -(0.791667 -(((data["loo_ps_car_11_cat"] * data["loo_ps_car_11_cat"])+ data["loo_ps_ind_02_cat"])/2.0))))
v["133"] = 0.020000*np.tanh(((data["ps_ind_14"] +(( data["loo_ps_ind_04_cat"] + data["ps_ind_15"])/2.0)) *(( data["ps_ind_15"] + data["loo_ps_ind_04_cat"])/2.0)))
 v["134"] = 0.020000*np.tanh(((0.791667 - data["ps_ind_01"])*(((data["ps_ind_03"] + data["loo_ps_ind_04_cat"])/2.0)* data["loo_ps_ind_05_cat"])))
 v["135"] = 0.019992*np.tanh(((-2.0 +(data["ps_car_12"] *(( data["ps_car_12"] - 1.089890)+ data["loo_ps_ind_04_cat"])))/2.0))
v["136"] = 0.019977*np.tanh(((data["loo_ps_car_09_cat"] *(data["loo_ps_car_01_cat"] *(data["loo_ps_ind_02_cat"] + data["loo_ps_ind_17_bin"])))- data["loo_ps_ind_02_cat"]))
v["137"] = 0.019996*np.tanh(((-1.0 +(( data["ps_reg_03"] * data["ps_reg_03"])* data["loo_ps_ind_05_cat"])) * data["loo_ps_ind_05_cat"]))
v["138"] = 0.020000*np.tanh(((( data["ps_car_11"] *(data["ps_ind_14"] - data["ps_car_12"])) + data["loo_ps_car_09_cat"])/2.0))
v["139"] = 0.019996*np.tanh(( data["loo_ps_car_07_cat"] *(((( data["missing"] * data["missing"])+ data["ps_ind_15"])/2.0)+ data["loo_ps_ind_17_bin"])))
 v["140"] = 0.020000*np.tanh(( data["ps_reg_01"] *(( data["ps_reg_01"] - data["ps_reg_03"])- data["loo_ps_ind_17_bin"])))
 v["141"] = 0.019996*np.tanh(((data["loo_ps_ind_04_cat"] -(( data["ps_car_13"] +(data["loo_ps_ind_05_cat"] * data["loo_ps_ind_05_cat"])) /2.0)) * data["loo_ps_car_07_cat"]))
v["142"] = 0.020000*np.tanh(((data["ps_ind_15"] +(((data["ps_reg_03"] * data["ps_reg_03"])- 0.432099)+ data["loo_ps_ind_16_bin"])) /2.0))
v["143"] = 0.020000*np.tanh(((data["loo_ps_ind_04_cat"] +(data["loo_ps_ind_08_bin"] -(data["loo_ps_car_04_cat"] +(data["loo_ps_ind_08_bin"] * data["ps_car_13"])))) /2.0))
v["144"] = 0.019996*np.tanh(((((-1.0 - data["ps_ind_03"])- data["ps_ind_03"])* data["loo_ps_ind_02_cat"])- 0.432099))
v["145"] = 0.020000*np.tanh(((( data["loo_ps_ind_02_cat"] *(data["loo_ps_ind_02_cat"] - 0.788462)) * data["loo_ps_ind_02_cat"])- data["loo_ps_car_10_cat"]))
v["146"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] *(( data["loo_ps_ind_04_cat"] + data["ps_ind_03"])*(0.791667 - data["ps_ind_03"]))))
v["147"] = 0.020000*np.tanh(( np.tanh(data["loo_ps_ind_05_cat"])*(((-(data["loo_ps_ind_18_bin"])) +(data["ps_car_14"] + data["missing"])) /2.0)))
 v["148"] = 0.020000*np.tanh(( data["ps_reg_03"] *(((data["loo_ps_ind_09_bin"] - data["loo_ps_ind_18_bin"])- data["ps_car_15"])- data["loo_ps_ind_02_cat"])))
 v["149"] = 0.020000*np.tanh(((data["loo_ps_ind_04_cat"] +(data["ps_ind_15"] *(-(( data["loo_ps_ind_17_bin"] - data["ps_ind_14"])))))/2.0))
v["150"] = 0.020000*np.tanh(((( data["loo_ps_ind_04_cat"] * data["loo_ps_car_03_cat"])+(-(((data["loo_ps_car_01_cat"] + data["loo_ps_car_10_cat"])/2.0)))) /2.0))
v["151"] = 0.020000*np.tanh(((0.666667 - data["ps_ind_03"])*(( data["loo_ps_car_07_cat"] +(data["ps_reg_01"] + data["ps_ind_15"])) /2.0)))
 v["152"] = 0.020000*np.tanh(((data["loo_ps_car_03_cat"] * data["loo_ps_ind_05_cat"])*(( data["loo_ps_car_06_cat"] +(( -1.0 + data["loo_ps_ind_04_cat"])/2.0)) /2.0)))
 v["153"] = 0.020000*np.tanh(((data["ps_ind_03"] * data["ps_ind_03"])*(-2.0 +(data["ps_ind_03"] * data["ps_ind_03"]))))
v["154"] = 0.020000*np.tanh(((data["loo_ps_ind_13_bin"] - data["loo_ps_ind_11_bin"])*(( data["loo_ps_ind_02_cat"] +(7.0)) * 29.500000)))
 v["155"] = 0.019977*np.tanh(((( data["loo_ps_ind_02_cat"] + data["loo_ps_car_08_cat"])*(data["loo_ps_ind_02_cat"] * 2.0)) - 1.089890))
v["156"] = 0.020000*np.tanh(((data["ps_car_12"] +(data["loo_ps_ind_16_bin"] *(( -(data["ps_reg_01"])) * data["loo_ps_car_05_cat"])))/2.0))
v["157"] = 0.020000*np.tanh(((( data["loo_ps_ind_04_cat"] - data["loo_ps_ind_05_cat"])+(data["loo_ps_ind_05_cat"] * data["ps_ind_15"])) /2.0))
v["158"] = 0.020000*np.tanh(((data["loo_ps_car_01_cat"] *(((data["loo_ps_car_02_cat"] + data["loo_ps_ind_17_bin"])/2.0)* data["loo_ps_ind_02_cat"])) * data["loo_ps_car_07_cat"]))
v["159"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(((data["loo_ps_ind_05_cat"] * data["loo_ps_ind_16_bin"])+ -3.0)* data["loo_ps_ind_04_cat"])))
 v["160"] = 0.020000*np.tanh(( data["loo_ps_car_05_cat"] *(( data["loo_ps_ind_02_cat"] +(-(( data["loo_ps_car_06_cat"] * data["loo_ps_car_02_cat"])))) /2.0)))
 v["161"] = 0.019961*np.tanh(( -(( data["loo_ps_car_03_cat"] *(0.753247 -(data["ps_ind_01"] * data["ps_ind_01"]))))))
v["162"] = 0.020000*np.tanh(((data["ps_car_13"] + data["loo_ps_ind_17_bin"])*(( data["ps_ind_03"] +(data["ps_ind_03"] + data["loo_ps_car_07_cat"])) /2.0)))
 v["163"] = 0.019988*np.tanh(((data["ps_ind_01"] +(( data["loo_ps_ind_09_bin"] +(( data["ps_ind_01"] + data["missing"])/2.0)) /2.0)) * data["missing"]))
v["164"] = 0.019988*np.tanh(( data["ps_reg_03"] *(-(((((data["loo_ps_ind_02_cat"] +(-(data["ps_reg_03"])))/2.0)+ data["ps_reg_01"])/2.0)))))
 v["165"] = 0.020000*np.tanh(((1.480000 +(data["loo_ps_ind_11_bin"] * 29.500000)) * 29.500000))
v["166"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] -(( 2.0 + data["ps_car_11"])*(2.352940 * 2.352940))))
v["167"] = 0.020000*np.tanh(((data["ps_car_11"] +(((-(data["loo_ps_car_04_cat"])) +(( data["loo_ps_ind_04_cat"] + data["loo_ps_car_02_cat"])/2.0)) /2.0)) /2.0))
v["168"] = 0.019996*np.tanh(((( data["loo_ps_car_09_cat"] *(-(data["ps_reg_01"])))+(data["ps_reg_01"] - data["ps_ind_03"])) /2.0))
v["169"] = 0.019996*np.tanh(( data["loo_ps_car_09_cat"] *(( data["loo_ps_car_09_cat"] * data["loo_ps_ind_17_bin"])-(0.791667 - data["ps_reg_02"]))))
v["170"] = 0.019992*np.tanh(((data["ps_car_15"] *(data["loo_ps_ind_06_bin"] - data["ps_ind_03"])) * data["loo_ps_car_04_cat"]))
v["171"] = 0.020000*np.tanh(((-(data["ps_reg_03"])) *(data["missing"] +(( data["loo_ps_car_03_cat"] + data["ps_car_14"])/2.0))))
v["172"] = 0.019996*np.tanh(( data["ps_ind_01"] *(( data["loo_ps_ind_05_cat"] *(( data["loo_ps_ind_02_cat"] + data["ps_ind_01"])/2.0)) - data["loo_ps_ind_04_cat"])))
 v["173"] = 0.019953*np.tanh(((data["ps_reg_01"] *(-(((data["loo_ps_ind_06_bin"] + np.tanh(data["loo_ps_ind_17_bin"])) /2.0)))) - data["loo_ps_car_10_cat"]))
v["174"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(((data["loo_ps_ind_02_cat"] * data["loo_ps_ind_02_cat"])- 0.887097)+ data["ps_ind_01"])))
 v["175"] = 0.020000*np.tanh(((( data["ps_reg_01"] +(data["loo_ps_car_01_cat"] * 0.117647)) /2.0)*(data["loo_ps_car_01_cat"] * data["loo_ps_car_01_cat"])))
 v["176"] = 0.019988*np.tanh(((( data["loo_ps_ind_04_cat"] * np.tanh(data["loo_ps_ind_17_bin"])) + np.tanh(( -3.0 + data["ps_car_13"])))/2.0))
v["177"] = 0.020000*np.tanh(( 1.089890 +(( 11.83836174011230469)*(( 0.666667 * 1.089890)- data["ps_car_15"]))))
v["178"] = 0.019996*np.tanh(((-1.0 +(data["loo_ps_ind_17_bin"] *(( data["loo_ps_ind_09_bin"] +(( data["loo_ps_ind_04_cat"] + -3.0)/2.0)) /2.0)))/2.0))
v["179"] = 0.020000*np.tanh(( data["loo_ps_car_03_cat"] *(data["loo_ps_car_04_cat"] *(data["loo_ps_ind_04_cat"] - np.tanh(data["ps_car_15"])))))
 v["180"] = 0.019887*np.tanh(( data["loo_ps_car_08_cat"] +(data["ps_ind_03"] *(data["loo_ps_car_02_cat"] * data["ps_ind_01"]))))
v["181"] = 0.020000*np.tanh(((((data["ps_reg_01"] +(-(data["ps_car_13"])))/2.0)* data["ps_ind_15"])* data["loo_ps_car_01_cat"]))
v["182"] = 0.020000*np.tanh(( data["ps_reg_01"] *(data["loo_ps_ind_07_bin"] *(((data["loo_ps_ind_02_cat"] + data["loo_ps_car_08_cat"])/2.0)- data["ps_reg_03"]))))
v["183"] = 0.020000*np.tanh(((( data["ps_ind_14"] +(data["loo_ps_ind_04_cat"] * data["loo_ps_ind_17_bin"])) /2.0)*(data["loo_ps_car_01_cat"] * data["loo_ps_ind_04_cat"])))
 v["184"] = 0.020000*np.tanh(( data["loo_ps_ind_17_bin"] *(( data["loo_ps_ind_02_cat"] +(data["ps_ind_15"] *(-(data["ps_car_15"])))) /2.0)))
 v["185"] = 0.019973*np.tanh(( data["loo_ps_ind_17_bin"] *(( data["loo_ps_car_01_cat"] - data["ps_ind_14"])*(data["ps_car_11"] + data["loo_ps_car_09_cat"]))))
v["186"] = 0.019918*np.tanh(( data["loo_ps_ind_02_cat"] *(((data["loo_ps_ind_02_cat"] * data["loo_ps_ind_02_cat"])- 0.666667)+ data["loo_ps_ind_18_bin"])))
 v["187"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(data["loo_ps_ind_04_cat"] *(data["ps_car_13"] +(data["loo_ps_car_04_cat"] + data["ps_car_12"])))))
 v["188"] = 0.020000*np.tanh(( data["loo_ps_car_07_cat"] *(data["loo_ps_ind_05_cat"] *(data["ps_car_13"] + data["ps_car_13"]))))
v["189"] = 0.019992*np.tanh(( data["ps_car_13"] *(data["loo_ps_car_01_cat"] *(data["ps_car_13"] - 2.0))))
v["190"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] *(data["loo_ps_ind_05_cat"] *(-(data["ps_reg_02"])))))
 v["191"] = 0.020000*np.tanh(( data["loo_ps_car_07_cat"] *(((data["loo_ps_ind_02_cat"] * 0.432099)* data["loo_ps_car_07_cat"])- data["loo_ps_car_02_cat"])))
 v["192"] = 0.020000*np.tanh(( data["ps_reg_01"] *(data["loo_ps_car_07_cat"] *(-(( data["loo_ps_ind_02_cat"] + data["loo_ps_ind_18_bin"]))))))
v["193"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] *(data["loo_ps_car_08_cat"] *(data["ps_reg_03"] -(( data["ps_ind_03"] + data["ps_ind_03"])/2.0)))))
 v["194"] = 0.019996*np.tanh(((data["ps_ind_03"] -(( 0.600000 + data["loo_ps_ind_08_bin"])/2.0)) *(( data["ps_ind_14"] + data["loo_ps_ind_08_bin"])/2.0)))
 v["195"] = 0.019992*np.tanh(((data["loo_ps_car_11_cat"] * data["loo_ps_car_04_cat"])*(((data["ps_ind_01"] + data["ps_ind_01"])+ data["loo_ps_ind_06_bin"])/2.0)))
 v["196"] = 0.019996*np.tanh(((data["loo_ps_car_04_cat"] -(( data["ps_ind_01"] + data["loo_ps_ind_02_cat"])/2.0)) *(data["loo_ps_ind_02_cat"] * data["ps_ind_03"])))
 v["197"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(data["ps_car_11"] *(( data["ps_reg_02"] - data["loo_ps_car_01_cat"])- data["loo_ps_car_03_cat"]))))
v["198"] = 0.020000*np.tanh(( data["ps_reg_03"] *(((( data["loo_ps_car_04_cat"] * data["loo_ps_car_08_cat"])+ data["loo_ps_ind_02_cat"])/2.0)* data["loo_ps_car_08_cat"])))
 v["199"] = 0.020000*np.tanh(((( data["ps_car_11"] + data["loo_ps_car_04_cat"])/2.0)*(( data["loo_ps_car_04_cat"] * data["loo_ps_ind_02_cat"])- data["loo_ps_car_04_cat"])))
 v["200"] = 0.019992*np.tanh(((( data["ps_car_13"] * data["ps_ind_14"])* data["ps_ind_15"])*(data["ps_car_13"] * data["ps_car_13"])))
 v["201"] = 0.019644*np.tanh(( data["ps_ind_15"] *(data["ps_reg_03"] +(( data["ps_ind_15"] * data["loo_ps_car_08_cat"])+ data["ps_reg_03"]))))
v["202"] = 0.020000*np.tanh(((-(( data["ps_reg_02"] *(( data["loo_ps_car_08_cat"] + data["ps_ind_15"])/2.0)))) * data["ps_ind_03"]))
v["203"] = 0.020000*np.tanh(( 0.666667 -(data["ps_car_15"] *(((data["loo_ps_car_08_cat"] + data["loo_ps_car_10_cat"])+ data["loo_ps_car_03_cat"])/2.0))))
v["204"] = 0.020000*np.tanh(((data["loo_ps_car_09_cat"] * np.tanh(data["loo_ps_car_02_cat"])) +(data["loo_ps_car_09_cat"] * data["loo_ps_car_11_cat"])))
 v["205"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] *(data["loo_ps_ind_08_bin"] -(( data["loo_ps_ind_18_bin"] * data["ps_reg_01"])* data["ps_reg_01"]))))
v["206"] = 0.019980*np.tanh(( data["loo_ps_ind_04_cat"] *(( data["loo_ps_car_01_cat"] -(data["loo_ps_ind_17_bin"] * data["loo_ps_car_01_cat"])) * data["ps_reg_02"])))
 v["207"] = 0.020000*np.tanh(((( data["loo_ps_ind_08_bin"] *(data["ps_ind_15"] + data["loo_ps_car_01_cat"])) - data["loo_ps_car_10_cat"])- data["loo_ps_car_10_cat"]))
v["208"] = 0.020000*np.tanh(( 0.148148 *(data["loo_ps_ind_02_cat"] *(-(( np.tanh(data["loo_ps_ind_18_bin"])* data["loo_ps_ind_16_bin"]))))))
v["209"] = 0.020000*np.tanh(((( data["ps_car_15"] + data["loo_ps_ind_04_cat"])/2.0)*(data["ps_car_12"] *(( data["loo_ps_ind_16_bin"] + data["ps_car_12"])/2.0))))
v["210"] = 0.020000*np.tanh(( data["loo_ps_car_11_cat"] *(data["loo_ps_ind_17_bin"] *(( data["loo_ps_ind_02_cat"] +(-(data["loo_ps_car_07_cat"])))/2.0))))
v["211"] = 0.020000*np.tanh(((data["ps_ind_03"] *(( data["loo_ps_ind_05_cat"] +(data["loo_ps_ind_02_cat"] * data["ps_ind_03"])) /2.0)) - data["loo_ps_ind_02_cat"]))
v["212"] = 0.019711*np.tanh(((((data["loo_ps_ind_09_bin"] * data["loo_ps_car_03_cat"])+(data["loo_ps_ind_09_bin"] * data["loo_ps_car_07_cat"])) /2.0)- 0.232323))
v["213"] = 0.020000*np.tanh(( data["ps_ind_03"] *(0.633333 -(( data["ps_ind_01"] + data["loo_ps_ind_02_cat"])* data["ps_ind_01"]))))
v["214"] = 0.020000*np.tanh(( data["loo_ps_ind_12_bin"] *(data["loo_ps_ind_11_bin"] +(( data["ps_ind_15"] + data["ps_reg_03"])+ data["ps_reg_03"]))))
v["215"] = 0.020000*np.tanh(( data["loo_ps_ind_16_bin"] *(( data["loo_ps_car_08_cat"] *(-(data["loo_ps_ind_02_cat"])))- data["loo_ps_car_07_cat"])))
 v["216"] = 0.020000*np.tanh(((((data["loo_ps_ind_17_bin"] + data["loo_ps_car_09_cat"])/2.0)* data["loo_ps_ind_05_cat"])* data["ps_reg_02"]))
v["217"] = 0.019984*np.tanh(( data["ps_car_14"] *(data["loo_ps_car_07_cat"] *(( data["ps_ind_15"] + data["loo_ps_ind_09_bin"])/2.0))))
v["218"] = 0.020000*np.tanh(((( data["loo_ps_ind_09_bin"] +(( data["loo_ps_ind_02_cat"] + data["ps_reg_02"])/2.0)) /2.0)*(( data["missing"] + data["ps_reg_02"])/2.0)))
 v["219"] = 0.019984*np.tanh(( data["ps_car_14"] *(( data["loo_ps_car_08_cat"] *(-(data["loo_ps_ind_04_cat"])))+(-(data["loo_ps_car_07_cat"])))))
 v["220"] = 0.020000*np.tanh(((( data["ps_ind_03"] *(( data["loo_ps_ind_02_cat"] * data["ps_ind_03"])* 2.0)) + data["ps_ind_03"])/2.0))
v["221"] = 0.019949*np.tanh(( data["loo_ps_ind_06_bin"] *(data["loo_ps_ind_16_bin"] *(( data["loo_ps_car_07_cat"] +(( data["ps_reg_02"] + data["loo_ps_ind_08_bin"])/2.0)) /2.0))))
v["222"] = 0.019984*np.tanh(((data["loo_ps_ind_17_bin"] * data["ps_reg_03"])*(-(((data["loo_ps_ind_12_bin"] + data["loo_ps_car_04_cat"])/2.0)))))
 v["223"] = 0.019848*np.tanh(((data["ps_ind_01"] *(data["loo_ps_ind_18_bin"] * data["loo_ps_car_01_cat"])) -(data["loo_ps_car_10_cat"] * data["ps_ind_03"])))
 v["224"] = 0.019973*np.tanh(((( data["ps_ind_03"] * 1.480000)* data["ps_reg_03"])*(( data["ps_car_12"] + data["loo_ps_ind_17_bin"])/2.0)))
 v["225"] = 0.020000*np.tanh(( -(( data["loo_ps_ind_17_bin"] *(data["ps_car_15"] -(data["loo_ps_ind_04_cat"] * data["loo_ps_car_10_cat"]))))))
v["226"] = 0.020000*np.tanh(((data["loo_ps_ind_04_cat"] + data["loo_ps_ind_04_cat"])*(data["ps_ind_01"] *(-(data["ps_ind_03"])))))
 v["227"] = 0.020000*np.tanh(( -(((( data["loo_ps_ind_06_bin"] +(data["loo_ps_car_08_cat"] + data["loo_ps_ind_02_cat"])) /2.0)* np.tanh(data["loo_ps_ind_18_bin"])))))
 v["228"] = 0.019988*np.tanh(( data["loo_ps_ind_07_bin"] *(data["loo_ps_ind_17_bin"] *(((data["loo_ps_car_08_cat"] + data["ps_reg_02"])+ data["loo_ps_ind_05_cat"])/2.0))))
v["229"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] *(data["ps_ind_15"] *(data["ps_car_12"] - np.tanh(0.753247)))))
 v["230"] = 0.014245*np.tanh(((( data["ps_reg_02"] + data["loo_ps_car_08_cat"])/2.0)*(data["ps_reg_02"] *(data["ps_reg_02"] - 3.0))))
v["231"] = 0.020000*np.tanh(((0.232323 +(data["loo_ps_car_11_cat"] *(data["ps_ind_01"] *(data["ps_reg_03"] * data["ps_reg_02"])))) /2.0))
v["232"] = 0.019984*np.tanh(( data["loo_ps_ind_08_bin"] *(-(((((data["ps_reg_03"] + data["loo_ps_car_11_cat"])/2.0)+ data["loo_ps_ind_12_bin"])/2.0)))))
 v["233"] = 0.019969*np.tanh(( -(np.tanh(( data["ps_reg_02"] *(data["loo_ps_car_06_cat"] -(data["ps_ind_03"] * data["loo_ps_ind_18_bin"])))))))
 v["234"] = 0.019996*np.tanh(( -(((data["ps_car_15"] +(( data["ps_car_14"] * data["loo_ps_car_02_cat"])- 0.753247)) /2.0))))
v["235"] = 0.020000*np.tanh(((data["loo_ps_car_07_cat"] *(-(data["loo_ps_ind_17_bin"])))*(data["loo_ps_car_02_cat"] + data["loo_ps_car_06_cat"])))
 v["236"] = 0.019984*np.tanh(( data["loo_ps_car_11_cat"] *(data["loo_ps_car_01_cat"] *(data["ps_reg_01"] *(( 0.791667 + data["loo_ps_car_07_cat"])/2.0)))))
 v["237"] = 0.020000*np.tanh(( data["loo_ps_car_08_cat"] *(((-(( data["loo_ps_car_03_cat"] * data["ps_ind_01"])))+ data["ps_ind_01"])/2.0)))
 v["238"] = 0.019973*np.tanh(( data["ps_car_11"] *(( data["loo_ps_car_06_cat"] +(data["ps_ind_03"] * np.tanh(( -(data["ps_car_11"])))))/2.0)))
 v["239"] = 0.020000*np.tanh(( data["loo_ps_car_01_cat"] *(data["loo_ps_car_06_cat"] *(((-(data["loo_ps_car_07_cat"])) + data["loo_ps_car_05_cat"])/2.0))))
v["240"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] *(data["ps_ind_01"] *(data["loo_ps_car_09_cat"] -(0.945455 - data["ps_ind_01"])))))
 v["241"] = 0.020000*np.tanh(((( data["loo_ps_ind_02_cat"] *(data["ps_ind_15"] - data["loo_ps_ind_02_cat"])) * data["ps_ind_15"])- data["loo_ps_ind_02_cat"]))
v["242"] = 0.019687*np.tanh(((-3.0 *(( data["ps_ind_15"] + 1.0)+ data["ps_ind_03"])) * data["loo_ps_car_09_cat"]))
v["243"] = 0.020000*np.tanh(((( 0.633333 * data["ps_car_14"])* data["loo_ps_ind_17_bin"])*(data["loo_ps_ind_04_cat"] - data["ps_car_12"])))
 v["244"] = 0.019930*np.tanh(( data["loo_ps_ind_08_bin"] *(( data["ps_ind_03"] +(( data["missing"] +(data["loo_ps_ind_04_cat"] - 1.0)) /2.0)) /2.0)))
 v["245"] = 0.019293*np.tanh(( data["loo_ps_ind_04_cat"] *(np.tanh(data["ps_car_12"])+(-(data["loo_ps_car_06_cat"])))))
 v["246"] = 0.020000*np.tanh(( data["loo_ps_ind_08_bin"] *(( data["loo_ps_ind_08_bin"] * data["loo_ps_ind_08_bin"])*(data["ps_ind_01"] - data["loo_ps_car_05_cat"]))))
v["247"] = 0.020000*np.tanh(( np.tanh(( data["ps_ind_15"] *(data["loo_ps_ind_07_bin"] + data["ps_ind_15"])))* data["loo_ps_ind_07_bin"]))
v["248"] = 0.019254*np.tanh(((((data["loo_ps_ind_08_bin"] +(data["ps_car_12"] * data["ps_ind_14"])) /2.0)+(data["loo_ps_ind_08_bin"] * data["loo_ps_car_03_cat"])) /2.0))
v["249"] = 0.019992*np.tanh(((data["loo_ps_ind_13_bin"] +(-(( data["ps_ind_03"] *(data["ps_car_14"] + data["loo_ps_ind_02_cat"])))))/2.0))
v["250"] = 0.020000*np.tanh(((data["loo_ps_ind_02_cat"] * data["loo_ps_car_08_cat"])*(data["loo_ps_car_03_cat"] -(data["loo_ps_ind_02_cat"] * data["loo_ps_ind_02_cat"]))))
v["251"] = 0.020000*np.tanh(((np.tanh(data["ps_car_12"])* data["loo_ps_ind_02_cat"])-(( data["loo_ps_ind_02_cat"] + np.tanh(data["loo_ps_ind_05_cat"])) /2.0)))
 v["252"] = 0.020000*np.tanh(((data["ps_ind_15"] * data["ps_ind_15"])*(data["loo_ps_ind_12_bin"] *(data["ps_ind_15"] * data["loo_ps_car_11_cat"]))))
v["253"] = 0.019801*np.tanh(((data["loo_ps_ind_05_cat"] - 0.232323)*(( data["loo_ps_ind_04_cat"] - data["ps_car_11"])* data["loo_ps_ind_17_bin"])))
 v["254"] = 0.020000*np.tanh(( data["loo_ps_ind_17_bin"] *(data["ps_ind_14"] *(-(( data["loo_ps_car_03_cat"] + data["loo_ps_ind_04_cat"]))))))
v["255"] = 0.019711*np.tanh(((( data["ps_car_11"] + data["ps_ind_01"])/2.0)*(-(( data["loo_ps_car_04_cat"] * np.tanh(data["ps_ind_01"]))))))
v["256"] = 0.019996*np.tanh(( data["loo_ps_ind_02_cat"] *(( data["ps_car_15"] * data["loo_ps_ind_17_bin"])*(data["missing"] - 0.945455))))
v["257"] = 0.020000*np.tanh(((( -(( data["missing"] * data["loo_ps_car_07_cat"])))+(data["loo_ps_car_07_cat"] *(-(data["loo_ps_ind_12_bin"])))) /2.0))
v["258"] = 0.019844*np.tanh(((data["loo_ps_ind_05_cat"] + data["ps_car_14"])*(-(( data["ps_ind_01"] * data["loo_ps_ind_17_bin"])))))
 v["259"] = 0.020000*np.tanh(( data["loo_ps_ind_08_bin"] *(((data["missing"] + np.tanh(data["loo_ps_ind_02_cat"])) /2.0)* data["ps_car_14"])))
 v["260"] = 0.019945*np.tanh(((data["loo_ps_ind_04_cat"] *(data["loo_ps_ind_04_cat"] +(-(data["loo_ps_ind_09_bin"])))) - data["loo_ps_car_10_cat"]))
v["261"] = 0.020000*np.tanh(((( data["ps_ind_03"] + data["loo_ps_ind_12_bin"])/2.0)*(data["ps_ind_03"] + np.tanh(( -(data["ps_ind_03"]))))))
v["262"] = 0.019992*np.tanh(( data["loo_ps_car_10_cat"] *(((data["loo_ps_ind_04_cat"] * data["loo_ps_ind_05_cat"])* data["ps_ind_01"])- data["ps_ind_01"])))
 v["263"] = 0.020000*np.tanh(( data["ps_reg_02"] *(( data["ps_car_13"] - data["loo_ps_car_07_cat"])*(data["ps_car_12"] - 0.633333))))
v["264"] = 0.019973*np.tanh(( data["ps_ind_14"] *(((8.428570 *(data["loo_ps_ind_07_bin"] * data["ps_car_15"])) + data["loo_ps_ind_13_bin"])/2.0)))
 v["265"] = 0.020000*np.tanh(((data["loo_ps_car_03_cat"] *(data["loo_ps_ind_05_cat"] - data["loo_ps_car_10_cat"])) * np.tanh(data["ps_reg_02"])))
 v["266"] = 0.020000*np.tanh(((( data["ps_car_13"] + np.tanh(data["loo_ps_ind_17_bin"])) /2.0)*(((-(data["loo_ps_car_10_cat"])) + data["loo_ps_ind_04_cat"])/2.0)))
 v["267"] = 0.020000*np.tanh(((data["ps_ind_03"] * data["loo_ps_ind_17_bin"])*(( -1.0 +(data["loo_ps_car_03_cat"] * data["ps_car_13"])) /2.0)))
 v["268"] = 0.019977*np.tanh(((((data["loo_ps_ind_11_bin"] +(data["ps_car_11"] + 1.480000)) /2.0)+ data["ps_ind_15"])* data["loo_ps_ind_12_bin"]))
v["269"] = 0.020000*np.tanh(( np.tanh(np.tanh(data["ps_reg_03"])) *(data["ps_car_11"] *(data["ps_ind_14"] + data["ps_ind_15"]))))
v["270"] = 0.018535*np.tanh(((( data["loo_ps_ind_05_cat"] +(data["loo_ps_ind_18_bin"] -(data["loo_ps_ind_05_cat"] * data["loo_ps_ind_18_bin"])))/2.0)* data["loo_ps_ind_09_bin"]))
v["271"] = 0.020000*np.tanh(( data["ps_car_15"] *(data["ps_car_12"] *(np.tanh(data["ps_car_15"])- data["ps_car_11"]))))
v["272"] = 0.019957*np.tanh(( data["ps_reg_02"] *(data["ps_reg_03"] *(-3.0 + data["ps_reg_02"]))))
v["273"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] - data["loo_ps_ind_12_bin"])*(( data["ps_car_15"] +(( data["loo_ps_ind_02_cat"] + data["loo_ps_ind_02_cat"])/2.0)) /2.0)))
 v["274"] = 0.020000*np.tanh(( data["loo_ps_car_10_cat"] *(( data["loo_ps_ind_17_bin"] * data["loo_ps_ind_02_cat"])- data["loo_ps_ind_16_bin"])))
 v["275"] = 0.020000*np.tanh(((( data["ps_ind_03"] +(-(( data["loo_ps_ind_09_bin"] * data["ps_ind_15"])))) /2.0)* data["loo_ps_ind_05_cat"]))
v["276"] = 0.019512*np.tanh(np.tanh(( data["ps_ind_03"] *(( data["ps_reg_03"] * data["ps_reg_03"])- 0.791667))))
v["277"] = 0.018703*np.tanh(( -(((0.633333 * data["loo_ps_ind_05_cat"])*(data["loo_ps_ind_16_bin"] * data["loo_ps_car_08_cat"])))))
 v["278"] = 0.019988*np.tanh(((data["loo_ps_ind_02_cat"] * data["ps_ind_03"])*(data["ps_ind_03"] * data["loo_ps_ind_06_bin"])))
 v["279"] = 0.019723*np.tanh(((( data["loo_ps_ind_09_bin"] * data["loo_ps_car_04_cat"])+(data["ps_ind_03"] * data["ps_car_13"])) * data["ps_car_15"]))
v["280"] = 0.020000*np.tanh(((data["loo_ps_ind_02_cat"] +(data["loo_ps_ind_02_cat"] + data["ps_ind_03"])) *(data["loo_ps_ind_13_bin"] - data["loo_ps_ind_02_cat"])))
 v["281"] = 0.019992*np.tanh(( data["loo_ps_ind_04_cat"] *(data["loo_ps_ind_05_cat"] *(data["ps_ind_01"] -(( 0.432099 + data["loo_ps_car_06_cat"])/2.0)))))
 v["282"] = 0.020000*np.tanh(( data["ps_reg_01"] *(((data["loo_ps_ind_05_cat"] *(-(data["ps_car_12"])))+ data["loo_ps_ind_11_bin"])/2.0)))
 v["283"] = 0.020000*np.tanh(((( -(data["ps_ind_03"])) * data["loo_ps_ind_05_cat"])* np.tanh(np.tanh(data["ps_ind_01"]))))
v["284"] = 0.018035*np.tanh(( data["ps_ind_03"] * np.tanh(( data["loo_ps_car_05_cat"] *(data["loo_ps_ind_16_bin"] - data["ps_ind_01"])))))
 v["285"] = 0.017937*np.tanh(( data["loo_ps_ind_04_cat"] *(( data["ps_car_11"] +(data["loo_ps_ind_04_cat"] - data["loo_ps_ind_16_bin"])) + data["ps_ind_03"])))
 v["286"] = 0.020000*np.tanh(( data["ps_car_13"] *(data["loo_ps_car_03_cat"] *(( data["loo_ps_ind_13_bin"] * data["ps_car_13"])* data["ps_car_13"]))))
v["287"] = 0.019140*np.tanh(( data["loo_ps_car_03_cat"] *(( data["loo_ps_car_02_cat"] *(data["ps_reg_02"] - data["ps_reg_01"])) * data["loo_ps_ind_04_cat"])))
 v["288"] = 0.019984*np.tanh(( data["loo_ps_car_06_cat"] *(data["loo_ps_ind_02_cat"] *(data["loo_ps_ind_02_cat"] *(-(data["loo_ps_ind_16_bin"]))))))
v["289"] = 0.017492*np.tanh(((( data["ps_car_11"] * data["loo_ps_car_06_cat"])+(( -(data["ps_car_11"])) * data["loo_ps_ind_17_bin"])) /2.0))
v["290"] = 0.019707*np.tanh(( data["loo_ps_ind_04_cat"] *(((data["loo_ps_ind_11_bin"] +(data["missing"] * data["loo_ps_car_07_cat"])) + data["missing"])/2.0)))
 v["291"] = 0.019598*np.tanh(((data["ps_reg_01"] * data["loo_ps_car_04_cat"])*(data["loo_ps_car_07_cat"] + data["loo_ps_ind_12_bin"])))
 v["292"] = 0.019855*np.tanh(((data["loo_ps_ind_02_cat"] * data["loo_ps_ind_16_bin"])*(data["loo_ps_ind_07_bin"] *(data["loo_ps_ind_18_bin"] + 0.232323))))
v["293"] = 0.020000*np.tanh(((data["loo_ps_car_04_cat"] * data["ps_reg_01"])* np.tanh(((-(data["loo_ps_car_08_cat"])) - data["loo_ps_car_09_cat"]))))
v["294"] = 0.019992*np.tanh(( data["ps_reg_02"] *(data["ps_car_13"] *(data["ps_car_15"] +(data["loo_ps_car_05_cat"] * data["ps_reg_03"])))))
 v["295"] = 0.020000*np.tanh(((data["loo_ps_ind_12_bin"] *(data["loo_ps_car_01_cat"] - data["loo_ps_car_07_cat"])) * data["ps_reg_02"]))
v["296"] = 0.020000*np.tanh(( -(( data["loo_ps_car_10_cat"] *(( data["ps_car_15"] + data["loo_ps_car_11_cat"])+ data["ps_ind_14"])))))
 v["297"] = 0.019977*np.tanh(((( data["loo_ps_car_07_cat"] +(0.435484 - data["loo_ps_ind_06_bin"])) /2.0)*(data["loo_ps_ind_08_bin"] * data["loo_ps_car_08_cat"])))
 v["298"] = 0.019941*np.tanh(( data["ps_car_14"] *(data["loo_ps_ind_04_cat"] +(np.tanh(data["loo_ps_ind_04_cat"])*(-(data["loo_ps_ind_07_bin"]))))))
v["299"] = 0.019117*np.tanh(( data["loo_ps_ind_06_bin"] *(( data["ps_ind_03"] + data["loo_ps_ind_04_cat"])* data["loo_ps_ind_17_bin"])))
 v["300"] = 0.020000*np.tanh(((data["loo_ps_ind_16_bin"] *(data["loo_ps_ind_04_cat"] *(data["ps_reg_01"] * data["loo_ps_car_07_cat"])))* data["loo_ps_ind_18_bin"]))
v["301"] = 0.019973*np.tanh(( -(( data["ps_car_11"] *(((data["loo_ps_ind_04_cat"] + data["loo_ps_car_02_cat"])/2.0)* data["loo_ps_ind_05_cat"])))))
 v["302"] = 0.020000*np.tanh(( data["ps_car_12"] *(( data["loo_ps_ind_12_bin"] * data["ps_car_12"])*(data["ps_car_11"] - data["loo_ps_car_08_cat"]))))
v["303"] = 0.020000*np.tanh(( data["loo_ps_ind_17_bin"] *(data["loo_ps_car_10_cat"] *(data["loo_ps_ind_04_cat"] -(data["ps_ind_03"] * data["loo_ps_ind_17_bin"])))))
 v["304"] = 0.017566*np.tanh(((data["ps_reg_03"] - data["loo_ps_car_03_cat"])*(data["ps_reg_01"] * data["loo_ps_ind_08_bin"])))
 v["305"] = 0.019973*np.tanh(( 8.428570 *(0.666667 -(data["loo_ps_car_10_cat"] *(8.428570 - 0.432099)))))
 v["306"] = 0.020000*np.tanh(np.tanh(np.tanh(( -3.0 *(((data["ps_reg_01"] - data["loo_ps_car_02_cat"])+ 2.0)/2.0)))))
 v["307"] = 0.020000*np.tanh(((data["ps_ind_01"] - data["ps_reg_01"])*(data["ps_reg_02"] * data["loo_ps_ind_04_cat"])))
 v["308"] = 0.020000*np.tanh(((( data["ps_car_12"] + data["ps_ind_14"])/2.0)*(data["loo_ps_ind_02_cat"] *(data["ps_car_12"] * data["loo_ps_ind_17_bin"]))))
v["309"] = 0.020000*np.tanh(((data["loo_ps_ind_02_cat"] * data["loo_ps_car_04_cat"])*(( data["loo_ps_ind_02_cat"] * data["loo_ps_ind_02_cat"])- data["loo_ps_ind_02_cat"])))
 v["310"] = 0.020000*np.tanh(((( data["ps_ind_14"] * data["ps_car_12"])+(data["loo_ps_ind_04_cat"] *(data["loo_ps_ind_04_cat"] + data["ps_ind_14"])))/2.0))
v["311"] = 0.017878*np.tanh(( data["ps_reg_03"] *(-(((data["ps_car_12"] +(data["loo_ps_car_09_cat"] * data["loo_ps_ind_08_bin"])) /2.0)))))
 v["312"] = 0.019973*np.tanh(( data["loo_ps_car_01_cat"] *(((data["loo_ps_car_01_cat"] + data["ps_reg_01"])/2.0)* data["ps_car_12"])))
 v["313"] = 0.018691*np.tanh(((data["ps_car_14"] * data["loo_ps_car_11_cat"])*(-(( data["ps_ind_14"] + data["loo_ps_ind_08_bin"])))))
 v["314"] = 0.019566*np.tanh(((1.0 - data["loo_ps_car_11_cat"])*(((data["missing"] * data["loo_ps_car_11_cat"])+ data["ps_car_14"])/2.0)))
 v["315"] = 0.015312*np.tanh(((data["missing"] +(((data["missing"] - data["loo_ps_ind_02_cat"])- data["loo_ps_ind_09_bin"])* data["ps_reg_01"])) /2.0))
v["316"] = 0.019980*np.tanh(( data["loo_ps_car_03_cat"] *(( data["loo_ps_car_11_cat"] * data["loo_ps_ind_04_cat"])* data["loo_ps_ind_05_cat"])))
 v["317"] = 0.016890*np.tanh(( data["loo_ps_car_07_cat"] *(( data["loo_ps_car_11_cat"] - data["ps_car_13"])- data["loo_ps_ind_06_bin"])))
 v["318"] = 0.020000*np.tanh(( data["ps_car_12"] *(( data["ps_reg_02"] * data["loo_ps_car_04_cat"])*(( data["ps_reg_02"] + data["ps_ind_03"])/2.0))))
v["319"] = 0.016683*np.tanh(np.tanh(( data["loo_ps_ind_16_bin"] *(data["loo_ps_ind_12_bin"] -(data["loo_ps_ind_17_bin"] * data["ps_ind_01"])))))
 v["320"] = 0.018222*np.tanh(((data["loo_ps_ind_13_bin"] * data["ps_car_12"])- np.tanh(( data["loo_ps_ind_02_cat"] + data["ps_car_14"]))))
v["321"] = 0.020000*np.tanh(((data["ps_ind_14"] * data["ps_car_11"])*(data["ps_reg_02"] -(( data["ps_car_11"] + data["ps_car_15"])/2.0))))
v["322"] = 0.019703*np.tanh(((( data["ps_ind_01"] +(-(data["loo_ps_car_08_cat"])))/2.0)*(data["loo_ps_ind_17_bin"] * data["ps_ind_01"])))
 v["323"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] *(data["ps_reg_01"] - 0.753247)) *(data["loo_ps_car_02_cat"] * data["loo_ps_car_02_cat"])))
 v["324"] = 0.020000*np.tanh(( data["ps_reg_01"] *(( data["loo_ps_car_11_cat"] +(( data["ps_reg_01"] +(-(data["loo_ps_car_04_cat"])))/2.0)) /2.0)))
 v["325"] = 0.019898*np.tanh(( -(((((data["loo_ps_ind_17_bin"] +(-(data["ps_car_12"])))/2.0)+ np.tanh(data["ps_car_12"])) /2.0))))
v["326"] = 0.019980*np.tanh(((data["loo_ps_ind_12_bin"] +(data["loo_ps_car_04_cat"] *(data["loo_ps_car_09_cat"] + 2.352940)))* data["loo_ps_ind_13_bin"]))
v["327"] = 0.019996*np.tanh(((((data["loo_ps_ind_08_bin"] * data["loo_ps_car_09_cat"])+(data["ps_reg_03"] * data["loo_ps_ind_08_bin"])) /2.0)* data["ps_car_15"]))
v["328"] = 0.020000*np.tanh(( data["ps_reg_03"] *(((np.tanh(data["ps_car_11"])+ data["loo_ps_car_09_cat"])/2.0)* np.tanh(data["loo_ps_ind_07_bin"]))))
v["329"] = 0.019996*np.tanh(((((( data["loo_ps_ind_02_cat"] + data["loo_ps_car_10_cat"])/2.0)+ data["ps_car_14"])/2.0)*(data["loo_ps_car_08_cat"] * data["ps_reg_02"])))
 v["330"] = 0.020000*np.tanh(((data["loo_ps_car_10_cat"] * data["ps_reg_02"])*(data["loo_ps_ind_18_bin"] -(data["ps_ind_14"] * data["loo_ps_ind_02_cat"]))))
v["331"] = 0.020000*np.tanh(((( data["ps_ind_14"] + np.tanh(data["ps_ind_01"])) /2.0)*(data["loo_ps_ind_17_bin"] * data["loo_ps_car_06_cat"])))
 v["332"] = 0.020000*np.tanh(((( data["ps_ind_15"] + data["loo_ps_ind_05_cat"])/2.0)* np.tanh(( data["loo_ps_ind_17_bin"] *(-(data["loo_ps_car_06_cat"]))))))
v["333"] = 0.020000*np.tanh(( data["loo_ps_ind_17_bin"] *(data["ps_car_15"] * np.tanh(( data["ps_ind_03"] + data["loo_ps_car_11_cat"])))))
 v["334"] = 0.020000*np.tanh(( data["ps_car_11"] *(((data["loo_ps_ind_11_bin"] + data["loo_ps_ind_10_bin"])/2.0)-(data["loo_ps_ind_05_cat"] * data["loo_ps_ind_04_cat"]))))
v["335"] = 0.019996*np.tanh(( data["ps_car_11"] *(( data["loo_ps_car_10_cat"] +(( data["ps_reg_02"] * data["ps_car_11"])* data["loo_ps_ind_18_bin"])) /2.0)))
 v["336"] = 0.020000*np.tanh(((data["ps_ind_03"] * data["loo_ps_ind_02_cat"])*(data["ps_ind_03"] - data["ps_ind_15"])))
 v["337"] = 0.019996*np.tanh(((( data["loo_ps_car_07_cat"] *(data["loo_ps_ind_13_bin"] - data["loo_ps_ind_11_bin"])) * data["loo_ps_car_07_cat"])* data["loo_ps_car_07_cat"]))
v["338"] = 0.019219*np.tanh(((data["loo_ps_ind_02_cat"] *(( data["loo_ps_ind_05_cat"] * data["loo_ps_ind_18_bin"])- data["loo_ps_ind_02_cat"])) - data["loo_ps_ind_02_cat"]))
v["339"] = 0.020000*np.tanh(( data["loo_ps_car_07_cat"] *(np.tanh(0.232323)-(np.tanh(data["loo_ps_car_01_cat"])+ data["loo_ps_ind_12_bin"]))))
v["340"] = 0.019047*np.tanh(((data["ps_ind_01"] *(data["ps_reg_01"] * data["loo_ps_car_06_cat"])) -(data["ps_ind_14"] * data["ps_reg_01"])))
 v["341"] = 0.019996*np.tanh(( data["loo_ps_car_10_cat"] *(( np.tanh(np.tanh(data["ps_car_12"])) - data["ps_car_13"])- data["loo_ps_ind_12_bin"])))
 v["342"] = 0.019996*np.tanh(( data["ps_car_14"] *(data["loo_ps_car_05_cat"] *(((data["loo_ps_car_05_cat"] + data["ps_car_15"])+ data["ps_reg_01"])/2.0))))
v["343"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(np.tanh(((-(data["loo_ps_car_07_cat"])) + data["ps_reg_02"])) + data["loo_ps_ind_10_bin"])))
 v["344"] = 0.019902*np.tanh(( data["ps_car_14"] *(( np.tanh(data["loo_ps_ind_05_cat"])* data["ps_ind_15"])- np.tanh(data["ps_reg_03"]))))
v["345"] = 0.019937*np.tanh(((data["ps_car_11"] *(data["ps_car_12"] * data["loo_ps_ind_09_bin"])) *(data["loo_ps_ind_11_bin"] - data["loo_ps_ind_18_bin"])))
 v["346"] = 0.019984*np.tanh(((data["loo_ps_car_06_cat"] *(0.232323 -(data["loo_ps_ind_05_cat"] * data["loo_ps_ind_05_cat"])))* data["loo_ps_ind_04_cat"]))
v["347"] = 0.020000*np.tanh(((data["loo_ps_ind_11_bin"] * data["ps_ind_03"])*(( data["loo_ps_ind_05_cat"] * data["ps_ind_03"])* data["ps_ind_03"])))
 v["348"] = 0.019934*np.tanh(( data["loo_ps_ind_16_bin"] *(data["loo_ps_ind_12_bin"] *(data["ps_car_13"] *(data["loo_ps_car_10_cat"] + data["loo_ps_car_03_cat"])))))
 v["349"] = 0.020000*np.tanh(((((data["ps_car_15"] + data["ps_ind_14"])/2.0)* data["loo_ps_ind_06_bin"])* data["ps_reg_02"]))
v["350"] = 0.019769*np.tanh(((((data["ps_ind_03"] - data["ps_reg_02"])* 0.117647)- data["loo_ps_car_10_cat"])* data["ps_ind_03"]))
v["351"] = 0.019992*np.tanh(( -(((0.232323 +(( data["loo_ps_car_03_cat"] * data["ps_ind_03"])* data["loo_ps_car_08_cat"])) /2.0))))
v["352"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(( data["ps_ind_03"] *(0.232323 - data["loo_ps_car_11_cat"])) * data["ps_ind_15"])))
 v["353"] = 0.019980*np.tanh(( np.tanh(data["ps_ind_03"])*(( data["ps_car_11"] +(data["ps_reg_03"] + np.tanh(data["missing"])))/2.0)))
 v["354"] = 0.019988*np.tanh(( data["ps_car_14"] *(((data["loo_ps_ind_12_bin"] + data["ps_car_12"])/2.0)* data["ps_reg_01"])))
 v["355"] = 0.019957*np.tanh(np.tanh(( data["loo_ps_car_07_cat"] *(0.633333 -(data["ps_reg_02"] * data["ps_reg_02"])))))
 v["356"] = 0.019977*np.tanh(( data["loo_ps_car_09_cat"] *(data["loo_ps_car_09_cat"] *(data["loo_ps_ind_16_bin"] *(data["ps_reg_01"] * data["ps_ind_15"])))))
 v["357"] = 0.019887*np.tanh(((-(((( data["ps_car_14"] * data["loo_ps_ind_12_bin"])+ data["ps_reg_03"])/2.0)))* np.tanh(data["loo_ps_car_06_cat"])))
 v["358"] = 0.019965*np.tanh(( data["loo_ps_ind_05_cat"] *(data["ps_reg_02"] *(( np.tanh(( -(data["ps_ind_15"])))+ data["loo_ps_car_09_cat"])/2.0))))
v["359"] = 0.020000*np.tanh(( data["loo_ps_ind_12_bin"] *(( data["loo_ps_ind_11_bin"] +(data["loo_ps_car_11_cat"] + data["ps_ind_15"])) - data["loo_ps_ind_02_cat"])))
 v["360"] = 0.020000*np.tanh(((( data["ps_reg_01"] + data["ps_car_13"])/2.0)*(data["ps_ind_01"] * data["loo_ps_ind_05_cat"])))
 v["361"] = 0.020000*np.tanh(( data["loo_ps_ind_08_bin"] *(-(( data["loo_ps_ind_05_cat"] *(data["ps_car_11"] -(-(data["ps_ind_03"]))))))))
v["362"] = 0.018640*np.tanh(((((-(((data["ps_car_15"] + data["ps_car_11"])/2.0)))+ data["loo_ps_car_05_cat"])/2.0)* data["loo_ps_ind_06_bin"]))
v["363"] = 0.019480*np.tanh(((( np.tanh(data["ps_reg_02"])*(( data["loo_ps_car_07_cat"] + data["loo_ps_ind_11_bin"])/2.0)) + np.tanh(data["loo_ps_car_07_cat"])) /2.0))
v["364"] = 0.020000*np.tanh(( data["ps_ind_14"] *(-(( 0.753247 -(( data["ps_ind_03"] + data["ps_ind_03"])/2.0))))))
v["365"] = 0.020000*np.tanh(((( data["ps_reg_02"] *(-(data["loo_ps_ind_05_cat"])))* data["ps_car_15"])* data["loo_ps_ind_05_cat"]))
v["366"] = 0.019992*np.tanh(( data["ps_ind_15"] *(data["loo_ps_ind_02_cat"] *(( data["loo_ps_ind_02_cat"] * data["ps_reg_01"])- data["ps_ind_03"]))))
v["367"] = 0.020000*np.tanh(( data["ps_car_15"] *(( 0.232323 +(( -(data["ps_ind_15"])) * data["ps_car_15"])) /2.0)))
 v["368"] = 0.019992*np.tanh(((( data["loo_ps_car_02_cat"] + data["loo_ps_car_02_cat"])- data["ps_car_11"])*(data["loo_ps_ind_02_cat"] * data["loo_ps_ind_04_cat"])))
 v["369"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(data["ps_ind_15"] *(( data["ps_ind_15"] +(data["ps_reg_01"] * data["ps_car_13"])) /2.0))))
v["370"] = 0.019840*np.tanh(( data["ps_car_12"] *(( data["ps_car_11"] + data["loo_ps_ind_12_bin"])*(-(np.tanh(data["ps_ind_01"]))))))
v["371"] = 0.020000*np.tanh(( data["loo_ps_ind_06_bin"] *(data["loo_ps_ind_12_bin"] *(data["ps_car_12"] +(data["ps_ind_03"] * data["loo_ps_ind_04_cat"])))))
 v["372"] = 0.017296*np.tanh(( data["ps_car_11"] *(( data["ps_reg_03"] + np.tanh(( data["loo_ps_car_04_cat"] - data["ps_car_11"])))/2.0)))
 v["373"] = 0.019992*np.tanh(((( data["loo_ps_ind_04_cat"] * data["ps_car_11"])+ np.tanh(( -(( data["ps_car_11"] * data["loo_ps_ind_05_cat"])))))/2.0))
v["374"] = 0.017175*np.tanh(( data["loo_ps_car_09_cat"] * np.tanh(((data["loo_ps_ind_16_bin"] + data["ps_reg_02"])+ data["loo_ps_ind_16_bin"]))))
v["375"] = 0.020000*np.tanh(( np.tanh(( 0.618557 - data["loo_ps_ind_06_bin"])) *(data["loo_ps_car_08_cat"] * data["loo_ps_ind_02_cat"])))
 v["376"] = 0.019992*np.tanh(( np.tanh(data["loo_ps_ind_05_cat"])*(((-(data["loo_ps_car_02_cat"])) +(data["loo_ps_car_02_cat"] * data["ps_reg_03"])) /2.0)))
 v["377"] = 0.019965*np.tanh(((-(data["loo_ps_car_04_cat"])) *(((data["ps_ind_03"] * data["ps_ind_03"])+(-(data["ps_car_15"])))/2.0)))
 v["378"] = 0.019777*np.tanh(( data["loo_ps_ind_17_bin"] *(data["loo_ps_ind_17_bin"] *(((data["loo_ps_ind_08_bin"] + data["loo_ps_ind_13_bin"])/2.0)* data["loo_ps_car_04_cat"]))))
v["379"] = 0.019996*np.tanh(( data["loo_ps_car_02_cat"] *(((data["loo_ps_car_01_cat"] + data["ps_car_11"])/2.0)*(( data["loo_ps_car_01_cat"] + data["ps_ind_15"])/2.0))))
v["380"] = 0.019988*np.tanh(( data["loo_ps_ind_02_cat"] *(data["ps_car_15"] *(data["ps_car_11"] +(data["ps_ind_15"] * data["ps_reg_01"])))))
 v["381"] = 0.020000*np.tanh(((0.0 +(data["loo_ps_ind_04_cat"] *(data["ps_reg_03"] *(data["loo_ps_car_04_cat"] * data["loo_ps_car_08_cat"])))) /2.0))
v["382"] = 0.019953*np.tanh(((data["loo_ps_car_01_cat"] * data["loo_ps_car_01_cat"])*(( data["ps_reg_01"] +(-(data["loo_ps_car_10_cat"])))/2.0)))
 v["383"] = 0.020000*np.tanh(( -(( data["ps_reg_03"] *(data["ps_ind_14"] *(data["loo_ps_car_04_cat"] * data["ps_reg_03"]))))))
v["384"] = 0.019078*np.tanh(np.tanh(((data["loo_ps_ind_06_bin"] * data["loo_ps_ind_05_cat"])*(( -(0.432099)) - data["ps_reg_01"]))))
v["385"] = 0.019934*np.tanh(( data["loo_ps_car_03_cat"] *(( -(data["ps_car_13"])) *(data["loo_ps_car_10_cat"] * data["ps_car_13"]))))
v["386"] = 0.019945*np.tanh(np.tanh(((data["ps_ind_03"] *(( -(data["loo_ps_ind_04_cat"])) - data["missing"])) * data["loo_ps_ind_07_bin"])))
 v["387"] = 0.019680*np.tanh(( data["loo_ps_car_01_cat"] *(((data["loo_ps_car_01_cat"] +(-(data["loo_ps_car_09_cat"])))/2.0)* np.tanh(data["loo_ps_ind_16_bin"]))))
v["388"] = 0.020000*np.tanh(( data["loo_ps_ind_12_bin"] *(( -(data["ps_ind_01"])) *(data["loo_ps_ind_08_bin"] * data["loo_ps_ind_17_bin"]))))
v["389"] = 0.020000*np.tanh(((( data["ps_ind_03"] * 0.232323)+ np.tanh(( data["ps_reg_03"] * np.tanh(data["loo_ps_car_04_cat"])))) /2.0))
v["390"] = 0.019988*np.tanh(( data["loo_ps_car_08_cat"] *(( data["loo_ps_car_01_cat"] +(data["loo_ps_car_09_cat"] *(data["loo_ps_ind_04_cat"] * data["loo_ps_car_06_cat"])))/2.0)))
 v["391"] = 0.019988*np.tanh(((data["loo_ps_ind_11_bin"] * data["ps_reg_03"])-(( data["loo_ps_ind_11_bin"] +(( data["loo_ps_ind_16_bin"] + data["loo_ps_ind_10_bin"])/2.0)) /2.0)))
 v["392"] = 0.020000*np.tanh(((data["loo_ps_ind_11_bin"] - data["loo_ps_car_10_cat"])*(data["loo_ps_car_08_cat"] + data["ps_car_13"])))
 v["393"] = 0.019992*np.tanh(((data["loo_ps_ind_05_cat"] *(( data["ps_ind_14"] +(data["ps_car_14"] * data["ps_reg_03"])) /2.0)) * data["loo_ps_car_01_cat"]))
v["394"] = 0.019238*np.tanh(((np.tanh(( -(data["missing"])))* data["loo_ps_ind_07_bin"])*(-(data["ps_reg_01"]))))
v["395"] = 0.019906*np.tanh(( -(( np.tanh(( data["ps_ind_14"] * data["loo_ps_ind_17_bin"])) *(data["loo_ps_ind_07_bin"] + data["loo_ps_ind_07_bin"])))))
 v["396"] = 0.019789*np.tanh(np.tanh(( -(( data["loo_ps_car_03_cat"] *(data["ps_ind_01"] *(2.0 - data["ps_ind_01"])))))))
 v["397"] = 0.019949*np.tanh(((data["ps_car_13"] *(0.148148 *(-(np.tanh(data["ps_ind_15"])))))* data["ps_car_13"]))
v["398"] = 0.019137*np.tanh(( data["loo_ps_ind_02_cat"] *(((-(data["ps_ind_03"])) *(-(data["ps_ind_03"])))- 1.0)))
 v["399"] = 0.019895*np.tanh(np.tanh(np.tanh(((data["loo_ps_car_05_cat"] * data["ps_ind_01"])+(( data["ps_ind_03"] + data["loo_ps_ind_18_bin"])/2.0)))))
 v["400"] = 0.015581*np.tanh(( -(( 0.232323 *(data["loo_ps_ind_07_bin"] *(data["loo_ps_ind_16_bin"] + data["loo_ps_car_02_cat"]))))))
v["0"] = -3.274750
return v<feature_engineering>
net = NNModel()
def get_GP2_features(data):
v = pd.DataFrame()
v["1"] = 0.020000*np.tanh(( 3.642860 *(( data["loo_ps_car_01_cat"] + data["loo_ps_ind_16_bin"])+(data["ps_reg_03"] + data["loo_ps_ind_06_bin"]))))
v["2"] = 0.020000*np.tanh(( 19.500000 *(((data["ps_car_15"] + data["loo_ps_ind_06_bin"])+ data["loo_ps_car_06_cat"])+ data["loo_ps_car_07_cat"])))
 v["3"] = 0.019996*np.tanh(( 19.500000 *(( data["ps_car_13"] +(data["loo_ps_car_11_cat"] + data["loo_ps_ind_05_cat"])) + data["ps_reg_02"])))
 v["4"] = 0.020000*np.tanh(((( data["ps_reg_03"] +(data["loo_ps_ind_05_cat"] + data["loo_ps_car_07_cat"])) + data["ps_car_12"])* 19.500000))
v["5"] = 0.020000*np.tanh(( data["loo_ps_ind_06_bin"] +(data["loo_ps_car_04_cat"] -(data["ps_ind_15"] -(data["loo_ps_ind_17_bin"] + data["loo_ps_car_01_cat"])))))
 v["6"] = 0.020000*np.tanh(((11.51410007476806641)*(data["loo_ps_car_11_cat"] +(((data["loo_ps_car_09_cat"] + data["ps_reg_03"])/2.0)+ data["loo_ps_ind_06_bin"]))))
v["7"] = 0.020000*np.tanh(( 19.500000 *(( data["ps_car_13"] +(( data["loo_ps_ind_05_cat"] +(data["loo_ps_ind_17_bin"] + data["loo_ps_car_01_cat"])) /2.0)) /2.0)))
 v["8"] = 0.020000*np.tanh(( 19.500000 *(((data["ps_reg_02"] + data["loo_ps_ind_09_bin"])+ 0.760563)+ data["loo_ps_car_05_cat"])))
 v["9"] = 0.020000*np.tanh(( 19.500000 *(( data["loo_ps_car_11_cat"] +(((data["loo_ps_ind_17_bin"] + data["loo_ps_ind_06_bin"])+ data["loo_ps_car_03_cat"])/2.0)) /2.0)))
 v["10"] = 0.020000*np.tanh(( 6.846150 *(data["loo_ps_ind_06_bin"] +(data["loo_ps_car_11_cat"] +(data["loo_ps_ind_17_bin"] + data["loo_ps_car_09_cat"])))))
 v["11"] = 0.020000*np.tanh(((9.75283908843994141)*(( data["ps_reg_03"] +(data["loo_ps_car_11_cat"] - data["ps_ind_15"])) + data["loo_ps_ind_04_cat"])))
 v["12"] = 0.020000*np.tanh(((data["ps_reg_02"] + data["loo_ps_car_03_cat"])+(( data["ps_car_13"] - data["ps_ind_15"])+ data["loo_ps_ind_05_cat"])))
 v["13"] = 0.020000*np.tanh(((8.49180412292480469)*(( data["loo_ps_ind_09_bin"] + data["loo_ps_car_07_cat"])+(data["loo_ps_car_09_cat"] + data["loo_ps_ind_06_bin"]))))
v["14"] = 0.020000*np.tanh(((6.0)*(((( data["loo_ps_ind_16_bin"] + data["loo_ps_ind_05_cat"])+ data["ps_reg_01"])/2.0)+ data["ps_car_13"])))
 v["15"] = 0.020000*np.tanh(( data["loo_ps_car_01_cat"] +(((data["ps_reg_01"] + data["ps_car_12"])+ data["loo_ps_car_03_cat"])- data["ps_ind_15"])))
 v["16"] = 0.020000*np.tanh(((data["loo_ps_car_08_cat"] +(data["loo_ps_car_04_cat"] +(data["loo_ps_ind_05_cat"] + data["loo_ps_ind_17_bin"])))* 3.642860))
v["17"] = 0.020000*np.tanh(( 19.500000 *(( 0.760563 +(data["ps_reg_02"] + data["ps_car_13"])) + data["ps_reg_03"])))
 v["18"] = 0.020000*np.tanh(( data["loo_ps_ind_07_bin"] +(( 9.29609489440917969)*(((data["loo_ps_car_03_cat"] + data["ps_reg_03"])+ data["ps_car_15"])/2.0))))
v["19"] = 0.020000*np.tanh(( 6.846150 *(( data["loo_ps_ind_05_cat"] + data["ps_car_13"])+(data["loo_ps_ind_17_bin"] + data["loo_ps_car_07_cat"]))))
v["20"] = 0.020000*np.tanh(( data["loo_ps_car_04_cat"] +(data["ps_car_15"] +(data["ps_reg_03"] +(data["loo_ps_car_03_cat"] - data["ps_ind_15"])))))
 v["21"] = 0.020000*np.tanh(( 6.846150 *(data["loo_ps_ind_05_cat"] +(( data["ps_car_13"] +(data["ps_ind_03"] + data["loo_ps_ind_17_bin"])) /2.0))))
v["22"] = 0.020000*np.tanh(( 19.500000 *(( data["loo_ps_ind_16_bin"] - data["ps_ind_15"])+(data["ps_reg_03"] + 0.600000))))
v["23"] = 0.020000*np.tanh(( 3.0 *(data["loo_ps_car_03_cat"] +(data["loo_ps_car_04_cat"] +(data["loo_ps_ind_05_cat"] + data["loo_ps_car_01_cat"])))))
 v["24"] = 0.020000*np.tanh(( 6.846150 *(((data["loo_ps_car_01_cat"] + data["ps_ind_03"])+(data["loo_ps_ind_05_cat"] + data["loo_ps_ind_17_bin"])) /2.0)))
 v["25"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] +(((data["loo_ps_ind_17_bin"] + data["ps_car_13"])+ data["ps_reg_01"])+ data["loo_ps_ind_09_bin"])))
 v["26"] = 0.020000*np.tanh(((data["loo_ps_ind_09_bin"] +(data["loo_ps_ind_17_bin"] +(data["loo_ps_ind_06_bin"] + data["loo_ps_ind_05_cat"])))* 19.500000))
v["27"] = 0.020000*np.tanh(((data["ps_reg_03"] +(data["loo_ps_ind_06_bin"] +(data["loo_ps_car_01_cat"] + 1.871790)))*(13.13490962982177734)))
 v["28"] = 0.020000*np.tanh(( 6.846150 *(data["loo_ps_ind_05_cat"] +(( data["loo_ps_ind_05_cat"] +(data["ps_car_13"] + data["loo_ps_ind_16_bin"])) /2.0))))
v["29"] = 0.020000*np.tanh(((data["ps_reg_02"] +(data["loo_ps_ind_17_bin"] +(data["loo_ps_car_11_cat"] + data["ps_car_15"])))- data["ps_ind_15"]))
v["30"] = 0.020000*np.tanh(((3.0 *(data["loo_ps_ind_05_cat"] +(data["loo_ps_car_09_cat"] + data["ps_ind_03"])))+ data["ps_car_13"]))
v["31"] = 0.020000*np.tanh(((8.0)*(( data["loo_ps_ind_09_bin"] + data["loo_ps_ind_05_cat"])+(data["ps_ind_03"] + data["loo_ps_car_07_cat"]))))
v["32"] = 0.020000*np.tanh(( data["ps_reg_02"] +(( data["ps_car_13"] + data["loo_ps_car_01_cat"])+(( 1.11309552192687988)+ data["loo_ps_car_07_cat"]))))
v["33"] = 0.020000*np.tanh(( 6.846150 *(((data["loo_ps_ind_05_cat"] - data["ps_ind_15"])+(( data["loo_ps_ind_16_bin"] + data["loo_ps_car_09_cat"])/2.0)) /2.0)))
 v["34"] = 0.020000*np.tanh(( 19.500000 *(( data["loo_ps_car_07_cat"] +(((data["ps_ind_03"] + data["loo_ps_ind_05_cat"])+ data["loo_ps_ind_06_bin"])/2.0)) /2.0)))
 v["35"] = 0.020000*np.tanh(((((data["loo_ps_ind_05_cat"] + data["loo_ps_car_07_cat"])+(data["loo_ps_ind_07_bin"] + data["loo_ps_car_11_cat"])) /2.0)* 19.500000))
v["36"] = 0.020000*np.tanh(((( data["loo_ps_ind_06_bin"] +(data["loo_ps_car_09_cat"] + data["loo_ps_ind_05_cat"])) + data["loo_ps_ind_16_bin"])* 19.500000))
v["37"] = 0.020000*np.tanh(((( 6.0)*(data["loo_ps_car_05_cat"] +(data["loo_ps_car_11_cat"] + data["loo_ps_ind_05_cat"])))+ data["ps_reg_02"]))
v["38"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] +(data["loo_ps_car_01_cat"] - data["ps_ind_15"])) +(( data["loo_ps_ind_17_bin"] + data["loo_ps_ind_09_bin"])/2.0)))
 v["39"] = 0.020000*np.tanh(((data["ps_reg_03"] +(data["ps_reg_02"] +(data["loo_ps_ind_06_bin"] - -2.0)))+ data["ps_ind_01"]))
v["40"] = 0.020000*np.tanh(( data["ps_car_13"] -(data["ps_ind_15"] -(( 5.0)*(data["loo_ps_car_09_cat"] + data["loo_ps_ind_09_bin"])))))
 v["41"] = 0.020000*np.tanh(((( data["loo_ps_car_09_cat"] +(data["ps_ind_03"] * data["ps_ind_03"])) + data["ps_ind_03"])*(8.21348762512207031)))
 v["42"] = 0.020000*np.tanh(((11.08931350708007812)*(((data["loo_ps_ind_05_cat"] + data["ps_car_15"])+ data["ps_ind_01"])+ data["loo_ps_car_09_cat"])))
 v["43"] = 0.020000*np.tanh(( 19.500000 *(data["loo_ps_car_09_cat"] +(( data["loo_ps_ind_04_cat"] - data["ps_ind_15"])+ data["loo_ps_car_05_cat"]))))
v["44"] = 0.020000*np.tanh(( 19.500000 *(( data["loo_ps_ind_17_bin"] + data["ps_reg_03"])+(data["loo_ps_car_07_cat"] * data["loo_ps_car_07_cat"]))))
v["45"] = 0.020000*np.tanh(( data["ps_car_13"] -(data["ps_ind_15"] -(( data["loo_ps_ind_05_cat"] *(10.0)) - data["ps_car_11"]))))
v["46"] = 0.020000*np.tanh(((2.0 *(( data["loo_ps_car_07_cat"] + data["ps_ind_01"])+ data["loo_ps_ind_09_bin"])) + data["loo_ps_ind_17_bin"]))
v["47"] = 0.020000*np.tanh(((( data["loo_ps_ind_02_cat"] +(data["loo_ps_ind_16_bin"] + data["loo_ps_ind_02_cat"])) - data["loo_ps_ind_18_bin"])*(10.0)))
 v["48"] = 0.020000*np.tanh(((( data["ps_ind_03"] +(data["ps_ind_03"] * data["ps_ind_03"])) *(14.62119007110595703)) *(14.62119007110595703)))
 v["49"] = 0.020000*np.tanh(((6.846150 *(data["loo_ps_car_01_cat"] + data["loo_ps_car_09_cat"])) +(data["ps_car_13"] + 1.135800)))
 v["50"] = 0.020000*np.tanh(((7.46593427658081055)*(( 7.46593427658081055)*(( data["ps_ind_03"] * data["ps_ind_03"])+ data["ps_ind_03"]))))
v["51"] = 0.020000*np.tanh(((data["loo_ps_ind_07_bin"] +(0.965909 - data["ps_ind_15"])) *(3.642860 - data["loo_ps_ind_06_bin"])))
 v["52"] = 0.020000*np.tanh(( data["loo_ps_ind_07_bin"] +(( 7.95933532714843750)*(data["loo_ps_car_07_cat"] -(data["ps_ind_03"] * data["loo_ps_ind_02_cat"])))))
 v["53"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] +(data["loo_ps_ind_17_bin"] +(data["loo_ps_ind_06_bin"] + -2.0)))* 6.846150))
v["54"] = 0.020000*np.tanh(((data["loo_ps_ind_09_bin"] +(data["loo_ps_car_07_cat"] +(( data["ps_reg_03"] + data["ps_car_13"])/2.0)))*(8.96369743347167969)))
 v["55"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] +(data["ps_ind_03"] -(data["ps_ind_03"] *(( 7.0)* data["loo_ps_ind_02_cat"])))))
 v["56"] = 0.020000*np.tanh(((4.0)*(data["ps_reg_02"] +(data["ps_reg_03"] +(( data["loo_ps_ind_02_cat"] + data["ps_car_15"])/2.0)))))
 v["57"] = 0.020000*np.tanh(((data["loo_ps_car_09_cat"] +(data["loo_ps_car_09_cat"] +(data["loo_ps_ind_05_cat"] * data["loo_ps_ind_06_bin"])))* 19.500000))
v["58"] = 0.020000*np.tanh(( 3.642860 *(data["loo_ps_ind_05_cat"] +(( data["loo_ps_car_05_cat"] * data["ps_ind_03"])- data["ps_car_11"]))))
v["59"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] +(data["loo_ps_car_07_cat"] +(( data["ps_ind_15"] * data["loo_ps_ind_18_bin"])* 6.846150))))
v["60"] = 0.020000*np.tanh(((( 6.846150 * data["loo_ps_ind_02_cat"])+(data["ps_ind_01"] + data["loo_ps_ind_07_bin"])) + data["loo_ps_car_01_cat"]))
v["61"] = 0.020000*np.tanh(((data["loo_ps_ind_17_bin"] +(data["loo_ps_ind_05_cat"] * data["ps_car_13"])) +(data["loo_ps_ind_17_bin"] - data["ps_ind_03"])))
 v["62"] = 0.020000*np.tanh(((( data["loo_ps_car_03_cat"] + data["ps_car_13"])+ data["loo_ps_car_04_cat"])*(data["loo_ps_ind_05_cat"] + data["loo_ps_ind_16_bin"])))
 v["63"] = 0.020000*np.tanh(((data["loo_ps_ind_17_bin"] * data["loo_ps_ind_09_bin"])+(data["loo_ps_ind_16_bin"] *(data["ps_ind_01"] + data["loo_ps_car_01_cat"]))))
v["64"] = 0.020000*np.tanh(( data["loo_ps_car_03_cat"] *(data["missing"] +(data["loo_ps_ind_17_bin"] +(data["ps_ind_01"] + data["loo_ps_car_11_cat"])))))
 v["65"] = 0.020000*np.tanh(((( data["ps_reg_02"] + data["loo_ps_ind_06_bin"])+ data["loo_ps_car_11_cat"])*(data["loo_ps_ind_05_cat"] - data["ps_car_11"])))
 v["66"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] - data["ps_reg_01"])*(data["ps_car_12"] +(data["loo_ps_car_11_cat"] + data["loo_ps_ind_17_bin"]))))
v["67"] = 0.020000*np.tanh(((data["loo_ps_ind_17_bin"] * data["loo_ps_ind_06_bin"])+(data["loo_ps_ind_04_cat"] +(( data["loo_ps_ind_08_bin"] + data["ps_car_13"])/2.0))))
v["68"] = 0.020000*np.tanh(((data["ps_car_13"] *(data["loo_ps_ind_05_cat"] - data["ps_car_11"])) +(data["loo_ps_ind_16_bin"] * data["loo_ps_ind_05_cat"])))
 v["69"] = 0.020000*np.tanh(((data["ps_ind_01"] *(data["loo_ps_car_05_cat"] - data["ps_ind_15"])) +(( data["loo_ps_car_07_cat"] + data["ps_car_13"])/2.0)))
 v["70"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] * 19.500000)*(data["loo_ps_ind_17_bin"] + data["ps_reg_02"])))
 v["71"] = 0.020000*np.tanh(( -1.0 +(data["loo_ps_ind_05_cat"] +(data["ps_ind_03"] *(data["ps_ind_03"] - data["loo_ps_ind_02_cat"])))))
 v["72"] = 0.020000*np.tanh(((( data["loo_ps_ind_06_bin"] + data["ps_car_13"])*(data["ps_ind_03"] + data["loo_ps_ind_05_cat"])) - data["ps_ind_03"]))
v["73"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] +(data["loo_ps_ind_16_bin"] *(data["loo_ps_car_09_cat"] +(data["ps_reg_02"] * data["ps_reg_02"])))))
 v["74"] = 0.020000*np.tanh(((( data["loo_ps_car_03_cat"] * 3.0)* 3.0)*(data["ps_ind_15"] + data["loo_ps_ind_17_bin"])))
 v["75"] = 0.020000*np.tanh(((( data["ps_ind_01"] + data["loo_ps_ind_17_bin"])/2.0)*(( data["loo_ps_car_07_cat"] - data["ps_car_11"])- data["ps_ind_15"])))
 v["76"] = 0.020000*np.tanh(((( data["loo_ps_car_09_cat"] -(data["loo_ps_car_04_cat"] * data["ps_car_11"])) + data["ps_reg_02"])- data["loo_ps_car_04_cat"]))
v["77"] = 0.019992*np.tanh(((((data["ps_ind_03"] - data["ps_ind_15"])* data["ps_car_12"])+ data["loo_ps_car_07_cat"])+ data["loo_ps_ind_04_cat"]))
v["78"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(( data["loo_ps_car_09_cat"] + data["ps_ind_01"])+(data["loo_ps_car_03_cat"] + data["ps_ind_01"]))))
v["79"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] + data["loo_ps_car_09_cat"])*(( data["loo_ps_ind_07_bin"] + data["loo_ps_ind_16_bin"])+ data["loo_ps_car_04_cat"])))
 v["80"] = 0.020000*np.tanh(((data["loo_ps_ind_17_bin"] + data["loo_ps_car_07_cat"])*(( data["loo_ps_car_09_cat"] + data["loo_ps_ind_09_bin"])+ data["ps_reg_02"])))
 v["81"] = 0.020000*np.tanh(((data["loo_ps_ind_04_cat"] +(data["loo_ps_car_03_cat"] * data["loo_ps_ind_09_bin"])) +(data["ps_ind_01"] * data["loo_ps_car_04_cat"])))
 v["82"] = 0.020000*np.tanh(((data["loo_ps_car_01_cat"] * data["loo_ps_car_05_cat"])-(data["ps_ind_15"] *(data["ps_car_13"] - data["loo_ps_ind_06_bin"]))))
v["83"] = 0.019996*np.tanh(((data["ps_ind_03"] *(( data["loo_ps_ind_09_bin"] - data["ps_reg_01"])- data["missing"])) - data["ps_car_11"]))
v["84"] = 0.020000*np.tanh(( data["loo_ps_car_02_cat"] +(((data["ps_car_13"] + data["loo_ps_car_09_cat"])/2.0)+(data["loo_ps_car_02_cat"] - data["ps_ind_03"]))))
v["85"] = 0.020000*np.tanh(( data["ps_ind_01"] +(data["ps_reg_01"] *(( data["missing"] - data["ps_ind_01"])- data["loo_ps_car_01_cat"]))))
v["86"] = 0.020000*np.tanh(((data["loo_ps_ind_17_bin"] -(( data["ps_reg_03"] + data["loo_ps_ind_09_bin"])/2.0)) *(data["loo_ps_car_01_cat"] - data["ps_ind_15"])))
 v["87"] = 0.020000*np.tanh(((data["loo_ps_ind_07_bin"] + data["loo_ps_ind_04_cat"])*(data["ps_ind_03"] +(( data["loo_ps_car_05_cat"] + data["loo_ps_car_09_cat"])/2.0))))
v["88"] = 0.020000*np.tanh(((data["loo_ps_ind_04_cat"] - data["loo_ps_car_04_cat"])+(( data["loo_ps_car_07_cat"] + data["loo_ps_ind_07_bin"])* data["loo_ps_ind_17_bin"])))
 v["89"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] * data["loo_ps_ind_17_bin"])+(( data["loo_ps_ind_05_cat"] - data["loo_ps_ind_02_cat"])* data["ps_ind_03"])))
 v["90"] = 0.020000*np.tanh(( data["ps_ind_03"] -(((data["ps_ind_03"] * data["loo_ps_ind_02_cat"])+ data["loo_ps_ind_02_cat"])* 6.846150)))
 v["91"] = 0.019980*np.tanh(( np.tanh(( -(data["loo_ps_car_11_cat"])))+(data["loo_ps_car_07_cat"] -(data["ps_ind_15"] * data["loo_ps_car_11_cat"]))))
v["92"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] +(( data["loo_ps_ind_05_cat"] *(data["ps_reg_02"] + data["loo_ps_ind_17_bin"])) - data["loo_ps_ind_05_cat"])))
 v["93"] = 0.019996*np.tanh(((data["loo_ps_ind_02_cat"] + data["loo_ps_ind_02_cat"])*(( data["loo_ps_car_08_cat"] - data["ps_ind_03"])+ data["loo_ps_car_08_cat"])))
 v["94"] = 0.020000*np.tanh(((( data["loo_ps_ind_05_cat"] *(data["loo_ps_ind_07_bin"] + data["ps_reg_02"])) +(data["loo_ps_ind_02_cat"] - data["ps_ind_03"])) /2.0))
v["95"] = 0.020000*np.tanh(((( data["loo_ps_car_09_cat"] + data["ps_reg_01"])/2.0)-(data["loo_ps_ind_06_bin"] *(data["ps_car_15"] + data["ps_reg_01"]))))
v["96"] = 0.020000*np.tanh(((data["loo_ps_ind_02_cat"] +(((data["loo_ps_car_09_cat"] + data["loo_ps_ind_18_bin"])/2.0)* data["loo_ps_ind_17_bin"])) * data["loo_ps_car_09_cat"]))
v["97"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(( data["loo_ps_ind_07_bin"] + data["ps_ind_15"])+(data["ps_ind_01"] + data["loo_ps_car_09_cat"]))))
v["98"] = 0.020000*np.tanh(( data["ps_reg_02"] +(((data["loo_ps_ind_02_cat"] - data["ps_ind_03"])* data["loo_ps_ind_02_cat"])+ -1.0)))
 v["99"] = 0.020000*np.tanh(((( data["ps_ind_03"] - data["ps_car_15"])- data["ps_ind_15"])*(( data["ps_car_15"] + data["ps_ind_03"])/2.0)))
 v["100"] = 0.020000*np.tanh(((((data["ps_reg_03"] + data["loo_ps_car_09_cat"])/2.0)+ data["loo_ps_ind_05_cat"])*(-2.0 + data["loo_ps_ind_05_cat"])))
 v["101"] = 0.020000*np.tanh(((( data["ps_car_15"] + data["loo_ps_car_09_cat"])/2.0)-(data["loo_ps_car_03_cat"] *(data["ps_car_15"] - data["loo_ps_ind_09_bin"]))))
v["102"] = 0.020000*np.tanh(( data["ps_ind_01"] +(data["loo_ps_ind_04_cat"] -(( data["ps_car_11"] + data["ps_ind_01"])* data["ps_ind_01"]))))
v["103"] = 0.019988*np.tanh(((( data["ps_reg_03"] *(data["loo_ps_ind_05_cat"] - data["ps_ind_01"])) +(( data["ps_car_13"] + data["loo_ps_ind_04_cat"])/2.0)) /2.0))
v["104"] = 0.020000*np.tanh(( data["loo_ps_car_08_cat"] +(data["loo_ps_car_03_cat"] *(( data["loo_ps_ind_04_cat"] + data["ps_reg_03"])+ data["ps_reg_03"]))))
v["105"] = 0.020000*np.tanh(((((data["loo_ps_ind_05_cat"] * data["loo_ps_ind_17_bin"])- data["loo_ps_car_07_cat"])+ data["loo_ps_ind_02_cat"])- data["loo_ps_ind_05_cat"]))
v["106"] = 0.019996*np.tanh(((data["ps_ind_01"] -(data["ps_car_15"] * data["loo_ps_ind_17_bin"])) +(( data["ps_ind_01"] + data["loo_ps_car_01_cat"])/2.0)))
 v["107"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] +(data["ps_ind_01"] + data["loo_ps_car_09_cat"])) *(data["loo_ps_ind_17_bin"] - data["ps_reg_01"])))
 v["108"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] *(data["ps_car_11"] +(( data["loo_ps_car_09_cat"] + data["ps_ind_03"])- data["loo_ps_ind_06_bin"]))))
v["109"] = 0.020000*np.tanh(((data["missing"] +(( data["loo_ps_ind_05_cat"] + data["ps_reg_02"])*(data["loo_ps_car_11_cat"] * data["loo_ps_car_05_cat"])))/2.0))
v["110"] = 0.019996*np.tanh(( data["ps_reg_03"] *(((data["ps_car_11"] + data["loo_ps_car_09_cat"])/2.0)-(( data["loo_ps_ind_02_cat"] + data["ps_reg_01"])/2.0))))
v["111"] = 0.019988*np.tanh(((-1.0 +(data["loo_ps_ind_02_cat"] * data["loo_ps_ind_02_cat"])) *(data["loo_ps_ind_02_cat"] + data["loo_ps_ind_02_cat"])))
 v["112"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(data["loo_ps_ind_05_cat"] -(1.526320 - np.tanh(( -(data["loo_ps_ind_05_cat"])))))))
 v["113"] = 0.020000*np.tanh(((((( data["loo_ps_ind_16_bin"] + data["loo_ps_car_01_cat"])/2.0)+ data["ps_ind_03"])/2.0)*(data["missing"] - data["ps_car_11"])))
 v["114"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] - data["ps_reg_01"])*(data["loo_ps_ind_08_bin"] +(data["ps_ind_01"] + data["loo_ps_car_04_cat"]))))
v["115"] = 0.020000*np.tanh(( -(( data["ps_reg_02"] *(data["loo_ps_ind_04_cat"] +(data["ps_reg_02"] * data["loo_ps_car_07_cat"]))))))
v["116"] = 0.020000*np.tanh(((data["ps_ind_03"] +(data["ps_ind_03"] + 3.0)) *(data["ps_ind_03"] + -2.0)))
 v["117"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] -(data["loo_ps_car_04_cat"] *(( data["ps_car_11"] + data["ps_ind_15"])+ 1.871790))))
v["118"] = 0.020000*np.tanh(( data["ps_reg_03"] *(data["ps_reg_03"] -(( 0.513158 - data["loo_ps_ind_07_bin"])* data["loo_ps_ind_16_bin"]))))
v["119"] = 0.020000*np.tanh(((((data["ps_reg_03"] + data["loo_ps_car_09_cat"])*(data["loo_ps_ind_05_cat"] - data["ps_reg_01"])) + data["ps_reg_01"])/2.0))
v["120"] = 0.020000*np.tanh(((((( data["missing"] + data["loo_ps_car_04_cat"])/2.0)+ data["loo_ps_car_03_cat"])/2.0)*(data["loo_ps_ind_02_cat"] + data["loo_ps_car_11_cat"])))
 v["121"] = 0.019988*np.tanh(((data["ps_ind_03"] *(data["ps_ind_03"] - data["ps_ind_01"])) +(data["ps_ind_03"] - data["ps_ind_01"])))
 v["122"] = 0.020000*np.tanh(((data["loo_ps_ind_02_cat"] *(data["loo_ps_ind_04_cat"] *(data["loo_ps_ind_02_cat"] - 2.800000)))- data["loo_ps_car_10_cat"]))
v["123"] = 0.020000*np.tanh(( data["loo_ps_car_05_cat"] *(data["ps_ind_01"] +(( data["loo_ps_ind_07_bin"] +(( data["loo_ps_ind_04_cat"] + data["ps_ind_03"])/2.0)) /2.0))))
v["124"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] *(data["ps_reg_02"] * data["ps_reg_01"])) -(0.452381 + data["loo_ps_ind_05_cat"])))
 v["125"] = 0.020000*np.tanh(( data["loo_ps_car_01_cat"] *(( data["loo_ps_car_01_cat"] +(( -3.0 * data["ps_car_13"])- data["loo_ps_ind_06_bin"])) /2.0)))
 v["126"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(( data["loo_ps_ind_02_cat"] +(data["ps_reg_03"] +(data["loo_ps_ind_09_bin"] - 0.965909)))/2.0)))
 v["127"] = 0.019988*np.tanh(((((data["loo_ps_ind_02_cat"] - data["loo_ps_car_07_cat"])+(data["loo_ps_car_04_cat"] * data["ps_car_12"])) /2.0)* 0.485294))
v["128"] = 0.020000*np.tanh(((( data["loo_ps_car_09_cat"] * data["loo_ps_car_09_cat"])- data["ps_reg_02"])*(( data["ps_reg_03"] + data["loo_ps_ind_04_cat"])/2.0)))
 v["129"] = 0.020000*np.tanh(((( data["ps_reg_03"] + data["ps_reg_03"])* np.tanh(data["ps_ind_03"])) - data["ps_ind_03"]))
v["130"] = 0.020000*np.tanh(((data["ps_reg_03"] * data["ps_reg_03"])*(( data["loo_ps_ind_17_bin"] + data["ps_car_13"])/2.0)))
 v["131"] = 0.020000*np.tanh(( data["ps_reg_01"] *(0.273684 -(( data["loo_ps_car_09_cat"] +(data["ps_reg_03"] - data["ps_reg_01"])) /2.0))))
v["132"] = 0.020000*np.tanh(((( data["loo_ps_ind_05_cat"] + data["loo_ps_car_05_cat"])/2.0)*(( data["ps_reg_03"] * data["ps_reg_03"])- 0.760563)))
 v["133"] = 0.020000*np.tanh(((( data["loo_ps_ind_02_cat"] *(-(data["ps_ind_03"])))*(-(data["ps_ind_03"])))- data["loo_ps_ind_02_cat"]))
v["134"] = 0.020000*np.tanh(((( data["loo_ps_car_09_cat"] + -3.0)/2.0)*(((( data["ps_car_11"] + 1.135800)/2.0)+ data["loo_ps_ind_02_cat"])/2.0)))
 v["135"] = 0.020000*np.tanh(( data["loo_ps_car_07_cat"] *(((2.0 +(data["loo_ps_ind_04_cat"] - data["loo_ps_car_07_cat"])) /2.0)- data["ps_car_13"])))
 v["136"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(((( data["loo_ps_ind_04_cat"] + data["ps_reg_03"])/2.0)+ np.tanh(data["ps_ind_03"])) /2.0)))
 v["137"] = 0.020000*np.tanh(((( data["ps_reg_01"] *(data["ps_reg_01"] - data["loo_ps_ind_18_bin"])) +(data["ps_car_11"] * data["loo_ps_car_06_cat"])) /2.0))
v["138"] = 0.019996*np.tanh(( data["loo_ps_ind_02_cat"] *(-3.0 +(data["ps_ind_03"] *(data["ps_ind_03"] + data["ps_ind_03"])))))
 v["139"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(( data["loo_ps_car_09_cat"] * data["loo_ps_car_09_cat"])+(data["ps_car_13"] * data["loo_ps_car_07_cat"]))))
v["140"] = 0.020000*np.tanh(((-(( data["ps_ind_03"] * data["loo_ps_ind_02_cat"])))- np.tanh(( data["loo_ps_ind_05_cat"] * data["loo_ps_ind_05_cat"]))))
v["141"] = 0.020000*np.tanh(( data["ps_car_13"] -(data["loo_ps_car_04_cat"] -(data["loo_ps_car_07_cat"] +(( data["loo_ps_ind_18_bin"] + data["loo_ps_car_07_cat"])/2.0)))))
 v["142"] = 0.020000*np.tanh(((( data["loo_ps_ind_02_cat"] - data["loo_ps_car_07_cat"])+(data["loo_ps_ind_17_bin"] *(data["ps_ind_03"] - data["ps_car_15"])))/2.0))
v["143"] = 0.020000*np.tanh(((((data["loo_ps_ind_02_cat"] + data["ps_car_13"])/2.0)- 1.135800)*(data["loo_ps_ind_02_cat"] + data["ps_car_13"])))
 v["144"] = 0.020000*np.tanh(((data["loo_ps_car_09_cat"] - data["ps_car_14"])*(data["loo_ps_car_02_cat"] +(data["loo_ps_car_05_cat"] * data["loo_ps_car_07_cat"]))))
v["145"] = 0.020000*np.tanh(((data["loo_ps_ind_04_cat"] - data["ps_ind_01"])*(data["loo_ps_ind_04_cat"] +(data["loo_ps_ind_04_cat"] - data["loo_ps_car_07_cat"]))))
v["146"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(data["loo_ps_ind_05_cat"] *(( data["loo_ps_ind_05_cat"] +(-2.0 - 0.452381)) /2.0))))
v["147"] = 0.020000*np.tanh(( -(((( data["loo_ps_ind_04_cat"] + data["loo_ps_ind_04_cat"])+ data["ps_car_15"])* data["ps_reg_02"]))))
v["148"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(( data["loo_ps_ind_02_cat"] *(data["loo_ps_ind_02_cat"] + data["loo_ps_car_08_cat"])) + data["loo_ps_car_08_cat"])))
 v["149"] = 0.020000*np.tanh(((data["loo_ps_ind_04_cat"] *(data["loo_ps_car_03_cat"] *(data["loo_ps_ind_04_cat"] + data["loo_ps_car_04_cat"])))- data["loo_ps_car_10_cat"]))
v["150"] = 0.020000*np.tanh(((data["missing"] *(( data["ps_ind_01"] +(( data["loo_ps_ind_02_cat"] + data["ps_ind_01"])/2.0)) /2.0)) - data["loo_ps_car_10_cat"]))
v["151"] = 0.020000*np.tanh(((( data["ps_ind_01"] *(data["ps_ind_01"] * data["loo_ps_car_03_cat"])) +(( data["ps_ind_03"] + data["loo_ps_ind_04_cat"])/2.0)) /2.0))
v["152"] = 0.019965*np.tanh(( data["ps_reg_01"] -(( data["ps_reg_01"] + data["loo_ps_ind_02_cat"])* data["ps_ind_03"])))
 v["153"] = 0.020000*np.tanh(((data["ps_ind_03"] * data["loo_ps_ind_05_cat"])*(-(( data["ps_ind_01"] - data["ps_reg_01"])))))
 v["154"] = 0.019988*np.tanh(((((( data["loo_ps_ind_04_cat"] + -1.0)/2.0)+ data["ps_ind_01"])/2.0)-(data["ps_car_11"] * data["ps_ind_01"])))
 v["155"] = 0.020000*np.tanh(((( data["loo_ps_car_07_cat"] +(( data["loo_ps_car_09_cat"] + data["ps_car_12"])/2.0)) /2.0)*(data["loo_ps_ind_06_bin"] * data["loo_ps_ind_16_bin"])))
 v["156"] = 0.020000*np.tanh(((data["loo_ps_car_01_cat"] - data["loo_ps_car_06_cat"])*(data["missing"] + data["loo_ps_ind_08_bin"])))
 v["157"] = 0.020000*np.tanh(((data["loo_ps_car_07_cat"] +(data["ps_car_12"] *(( data["loo_ps_car_01_cat"] - data["loo_ps_car_07_cat"])- data["loo_ps_car_07_cat"])))/2.0))
v["158"] = 0.020000*np.tanh(((( data["loo_ps_car_01_cat"] *(data["loo_ps_car_01_cat"] * 0.020833)) +(data["ps_car_15"] * data["missing"])) /2.0))
v["159"] = 0.020000*np.tanh(((0.093750 - data["ps_reg_01"])*(data["loo_ps_car_09_cat"] *(data["ps_car_12"] + data["loo_ps_car_09_cat"]))))
v["160"] = 0.020000*np.tanh(((( data["loo_ps_ind_09_bin"] +(data["loo_ps_car_09_cat"] *(data["loo_ps_car_05_cat"] * data["loo_ps_car_04_cat"])))/2.0)* data["loo_ps_car_09_cat"]))
v["161"] = 0.019977*np.tanh(((( -(( data["loo_ps_car_01_cat"] * data["ps_reg_03"])))- data["ps_car_12"])- data["ps_ind_14"]))
v["162"] = 0.020000*np.tanh(((((data["loo_ps_car_01_cat"] * data["loo_ps_car_01_cat"])*(data["loo_ps_car_01_cat"] - data["loo_ps_car_07_cat"])) + 0.760563)/2.0))
v["163"] = 0.019988*np.tanh(((( data["loo_ps_ind_02_cat"] +(( data["ps_car_12"] - 0.513158)- data["loo_ps_ind_06_bin"])) /2.0)- data["loo_ps_car_10_cat"]))
v["164"] = 0.020000*np.tanh(( data["ps_car_15"] +(data["loo_ps_ind_02_cat"] *(( data["loo_ps_car_07_cat"] * data["loo_ps_car_07_cat"])* data["loo_ps_car_01_cat"]))))
v["165"] = 0.019988*np.tanh(((( data["loo_ps_ind_04_cat"] +(data["loo_ps_car_07_cat"] - data["ps_car_15"])) /2.0)+(data["loo_ps_ind_09_bin"] * data["loo_ps_car_07_cat"])))
 v["166"] = 0.020000*np.tanh(((( data["loo_ps_car_10_cat"] + data["loo_ps_car_01_cat"])* data["loo_ps_ind_17_bin"])*(data["loo_ps_car_09_cat"] + data["loo_ps_ind_04_cat"])))
 v["167"] = 0.018984*np.tanh(((( 10.63927078247070312)*(-(data["loo_ps_ind_05_cat"])))*(( data["ps_reg_01"] + np.tanh(data["loo_ps_ind_16_bin"])) /2.0)))
 v["168"] = 0.020000*np.tanh(((( data["loo_ps_car_07_cat"] + data["ps_ind_03"])/2.0)*(((data["loo_ps_ind_17_bin"] * data["loo_ps_ind_04_cat"])+ data["ps_ind_03"])/2.0)))
 v["169"] = 0.020000*np.tanh(((((-1.0 +(data["loo_ps_ind_05_cat"] - 0.347826)) /2.0)+(data["ps_ind_15"] * data["ps_reg_01"])) /2.0))
v["170"] = 0.020000*np.tanh(( data["loo_ps_ind_16_bin"] *(( 0.100000 * data["loo_ps_car_01_cat"])-(( data["loo_ps_car_10_cat"] + 0.166667)/2.0))))
v["171"] = 0.020000*np.tanh(((data["loo_ps_car_05_cat"] * data["loo_ps_ind_17_bin"])*(( data["loo_ps_ind_04_cat"] * data["loo_ps_ind_04_cat"])- data["ps_car_11"])))
 v["172"] = 0.019992*np.tanh(( data["loo_ps_ind_07_bin"] *(data["ps_reg_03"] +(-(((data["loo_ps_car_01_cat"] + np.tanh(data["loo_ps_car_02_cat"])) /2.0))))))
v["173"] = 0.020000*np.tanh(((((( data["loo_ps_ind_04_cat"] + data["loo_ps_ind_05_cat"])/2.0)+ data["loo_ps_ind_08_bin"])/2.0)*(data["loo_ps_car_09_cat"] + data["ps_ind_03"])))
 v["174"] = 0.019988*np.tanh(((((data["loo_ps_ind_04_cat"] + data["ps_ind_14"])/2.0)-(( data["loo_ps_car_03_cat"] + 1.526320)/2.0)) * data["loo_ps_ind_04_cat"]))
v["175"] = 0.020000*np.tanh(( data["loo_ps_ind_17_bin"] *(((( data["loo_ps_ind_02_cat"] +(-(data["loo_ps_ind_12_bin"])))/2.0)+ data["loo_ps_car_05_cat"])/2.0)))
 v["176"] = 0.019902*np.tanh(((data["ps_reg_03"] +(data["ps_reg_03"] + np.tanh(data["loo_ps_ind_05_cat"])))*(-(data["loo_ps_car_11_cat"]))))
v["177"] = 0.019996*np.tanh(((( data["ps_reg_02"] + data["loo_ps_ind_02_cat"])/2.0)*(data["ps_car_12"] +(data["loo_ps_ind_05_cat"] * data["loo_ps_ind_16_bin"]))))
v["178"] = 0.020000*np.tanh(( data["ps_ind_15"] *(data["ps_ind_03"] *(-(((data["ps_reg_01"] + data["ps_ind_01"])/2.0))))))
v["179"] = 0.020000*np.tanh(((data["loo_ps_car_01_cat"] * data["loo_ps_car_11_cat"])*(data["ps_ind_03"] +(( data["ps_reg_01"] + data["loo_ps_car_01_cat"])/2.0))))
v["180"] = 0.020000*np.tanh(((( data["loo_ps_ind_04_cat"] +(-(data["loo_ps_ind_16_bin"])))/2.0)-(data["ps_reg_03"] * data["ps_reg_01"])))
 v["181"] = 0.020000*np.tanh(((data["loo_ps_ind_04_cat"] +(data["loo_ps_car_04_cat"] *(0.583333 -(data["ps_ind_03"] * data["ps_ind_03"])))) /2.0))
v["182"] = 0.019992*np.tanh(((data["ps_reg_03"] * data["ps_reg_03"])+ np.tanh(( data["ps_ind_03"] * data["loo_ps_ind_04_cat"]))))
v["183"] = 0.019961*np.tanh(((data["ps_ind_15"] *(np.tanh(( -(data["loo_ps_car_11_cat"])))- data["loo_ps_car_09_cat"])) * data["loo_ps_car_11_cat"]))
v["184"] = 0.020000*np.tanh(((( data["loo_ps_ind_16_bin"] + data["loo_ps_ind_07_bin"])/2.0)*(( data["missing"] +(-(data["ps_reg_01"])))/2.0)))
 v["185"] = 0.019949*np.tanh(( data["loo_ps_car_04_cat"] *(( data["ps_reg_03"] +(data["loo_ps_ind_02_cat"] - data["loo_ps_car_04_cat"])) /2.0)))
 v["186"] = 0.020000*np.tanh(((( data["ps_car_12"] + data["loo_ps_car_03_cat"])/2.0)*(((data["ps_car_12"] + data["loo_ps_ind_05_cat"])/2.0)* data["loo_ps_car_04_cat"])))
 v["187"] = 0.020000*np.tanh(( np.tanh(data["loo_ps_ind_17_bin"])*(data["loo_ps_ind_05_cat"] *(( data["loo_ps_ind_04_cat"] +(-(data["ps_ind_15"])))/2.0))))
v["188"] = 0.020000*np.tanh(((( data["ps_ind_03"] + data["loo_ps_ind_12_bin"])/2.0)*(data["ps_ind_03"] - np.tanh(data["ps_ind_03"]))))
v["189"] = 0.020000*np.tanh(((((data["loo_ps_car_11_cat"] + data["loo_ps_ind_04_cat"])/2.0)* data["loo_ps_ind_17_bin"])*(data["loo_ps_ind_02_cat"] - data["loo_ps_car_07_cat"])))
 v["190"] = 0.020000*np.tanh(((data["ps_ind_01"] * data["ps_ind_01"])*(((data["loo_ps_car_01_cat"] + data["ps_ind_03"])/2.0)* data["loo_ps_ind_17_bin"])))
 v["191"] = 0.020000*np.tanh(((( data["loo_ps_ind_02_cat"] +(-(data["ps_car_15"])))/2.0)* data["ps_car_15"]))
v["192"] = 0.020000*np.tanh(((0.166667 +(((data["ps_car_12"] + data["loo_ps_ind_17_bin"])/2.0)*(data["loo_ps_ind_04_cat"] * data["loo_ps_ind_04_cat"])))/2.0))
v["193"] = 0.019980*np.tanh(( data["loo_ps_car_02_cat"] *(((data["loo_ps_ind_13_bin"] + data["loo_ps_car_02_cat"])/2.0)-(data["ps_reg_02"] + data["loo_ps_car_06_cat"]))))
v["194"] = 0.019895*np.tanh(((data["ps_reg_03"] *(-(( data["ps_ind_03"] * data["ps_ind_15"])))) * data["loo_ps_car_01_cat"]))
v["195"] = 0.020000*np.tanh(( -(((((data["loo_ps_ind_04_cat"] + data["ps_ind_01"])/2.0)* data["ps_ind_01"])* data["ps_ind_03"]))))
v["196"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] *(-(data["ps_car_11"])))*(data["loo_ps_car_02_cat"] + data["loo_ps_car_01_cat"])))
 v["197"] = 0.020000*np.tanh(( np.tanh(data["loo_ps_car_01_cat"])*(data["ps_ind_14"] +(-(( data["loo_ps_ind_18_bin"] * data["loo_ps_car_09_cat"]))))))
v["198"] = 0.018046*np.tanh(( 19.500000 *(0.583333 -(6.846150 * data["loo_ps_car_10_cat"]))))
v["199"] = 0.019988*np.tanh(( -2.0 +(((data["loo_ps_car_10_cat"] + 0.965909)+ data["ps_car_11"])* data["ps_car_11"])))
 v["200"] = 0.020000*np.tanh(((data["ps_ind_03"] +(( data["ps_ind_03"] * data["ps_ind_01"])*(data["ps_car_13"] - data["ps_ind_01"])))/2.0))
v["201"] = 0.019984*np.tanh(( data["ps_reg_02"] *(((( -(data["loo_ps_car_01_cat"])) + data["loo_ps_ind_05_cat"])/2.0)* data["loo_ps_ind_17_bin"])))
 v["202"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(((( 0.965909 - data["loo_ps_car_01_cat"])+ data["loo_ps_ind_02_cat"])/2.0)* data["ps_ind_01"])))
 v["203"] = 0.020000*np.tanh(( data["ps_reg_03"] *(( data["ps_ind_15"] *(data["ps_ind_15"] + data["loo_ps_ind_09_bin"])) + data["ps_ind_15"])))
 v["204"] = 0.020000*np.tanh(((( data["loo_ps_car_10_cat"] + data["loo_ps_car_03_cat"])/2.0)*(-(((data["loo_ps_ind_18_bin"] + data["ps_car_15"])/2.0)))))
 v["205"] = 0.020000*np.tanh(((( -(np.tanh(data["loo_ps_ind_02_cat"])))+(((data["ps_ind_03"] + data["loo_ps_ind_02_cat"])/2.0)* data["loo_ps_ind_16_bin"])) /2.0))
v["206"] = 0.020000*np.tanh(np.tanh(( 19.500000 * np.tanh(( data["ps_ind_14"] +(0.965909 - data["ps_car_15"]))))))
v["207"] = 0.019945*np.tanh(((19.500000 -(data["loo_ps_ind_02_cat"] * 19.500000)) *(data["ps_reg_02"] - 2.800000)))
 v["208"] = 0.019969*np.tanh(((( data["ps_reg_02"] *(data["loo_ps_car_01_cat"] * data["loo_ps_ind_12_bin"])) +(data["loo_ps_car_11_cat"] * data["loo_ps_car_08_cat"])) /2.0))
v["209"] = 0.019996*np.tanh(((( data["ps_ind_03"] + data["loo_ps_ind_12_bin"])/2.0)*(( data["ps_ind_03"] +(data["missing"] - data["loo_ps_ind_02_cat"])) /2.0)))
 v["210"] = 0.020000*np.tanh(( data["loo_ps_ind_17_bin"] *(data["loo_ps_ind_04_cat"] *(data["ps_reg_03"] *(-(data["loo_ps_car_07_cat"]))))))
v["211"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(data["ps_reg_03"] +(( data["loo_ps_ind_02_cat"] * data["loo_ps_ind_09_bin"])- 0.600000))))
v["212"] = 0.017421*np.tanh(np.tanh(((-(( data["ps_car_11"] + data["loo_ps_ind_08_bin"])))* data["loo_ps_ind_05_cat"])))
 v["213"] = 0.019305*np.tanh(((( data["loo_ps_ind_02_cat"] * data["loo_ps_car_04_cat"])-(( data["missing"] + data["loo_ps_car_04_cat"])/2.0)) - data["loo_ps_ind_02_cat"]))
v["214"] = 0.019992*np.tanh(( data["ps_car_12"] *(((-(data["ps_car_11"])) +(data["ps_reg_01"] + data["loo_ps_ind_04_cat"])) /2.0)))
 v["215"] = 0.019879*np.tanh(( data["loo_ps_ind_05_cat"] *(data["ps_car_13"] *(( data["ps_car_14"] * data["ps_ind_15"])+ data["loo_ps_ind_05_cat"]))))
v["216"] = 0.019984*np.tanh(((data["loo_ps_car_01_cat"] * data["loo_ps_ind_17_bin"])*(data["loo_ps_ind_02_cat"] - data["loo_ps_ind_17_bin"])))
 v["217"] = 0.020000*np.tanh(((( data["ps_reg_03"] * data["loo_ps_car_08_cat"])- np.tanh(np.tanh(data["loo_ps_car_11_cat"])))* data["loo_ps_ind_05_cat"]))
v["218"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] +(0.273684 - data["loo_ps_ind_12_bin"])) *(data["ps_reg_02"] * data["loo_ps_car_07_cat"])))
 v["219"] = 0.020000*np.tanh(((((data["loo_ps_ind_16_bin"] +(data["loo_ps_ind_06_bin"] * 0.166667)) /2.0)* data["loo_ps_ind_06_bin"])* data["loo_ps_ind_05_cat"]))
v["220"] = 0.020000*np.tanh(((data["ps_ind_15"] * data["ps_car_15"])*(-(data["loo_ps_ind_17_bin"]))))
v["221"] = 0.020000*np.tanh(((((data["loo_ps_car_02_cat"] * data["ps_ind_03"])+(data["loo_ps_car_02_cat"] * data["ps_reg_01"])) /2.0)* data["ps_ind_01"]))
v["222"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(data["loo_ps_ind_18_bin"] *(data["loo_ps_ind_07_bin"] -(data["loo_ps_ind_04_cat"] * data["loo_ps_ind_16_bin"])))))
 v["223"] = 0.020000*np.tanh(((data["loo_ps_ind_12_bin"] * data["ps_car_11"])+(data["loo_ps_ind_04_cat"] *(data["ps_reg_01"] * data["loo_ps_car_08_cat"]))))
v["224"] = 0.019988*np.tanh(( data["ps_car_14"] *(( data["ps_car_14"] +(( data["loo_ps_ind_05_cat"] * data["loo_ps_ind_05_cat"])* data["loo_ps_car_01_cat"])) /2.0)))
 v["225"] = 0.019090*np.tanh(( data["ps_ind_15"] *(data["loo_ps_ind_07_bin"] -(-(( data["loo_ps_car_06_cat"] * data["ps_ind_15"]))))))
v["226"] = 0.015734*np.tanh(( data["ps_ind_15"] -(6.846150 *(( data["loo_ps_car_11_cat"] + data["loo_ps_car_06_cat"])+ data["loo_ps_car_06_cat"]))))
v["227"] = 0.020000*np.tanh(((data["ps_car_12"] - data["loo_ps_car_06_cat"])*(data["loo_ps_ind_02_cat"] *(-(data["loo_ps_car_08_cat"])))))
 v["228"] = 0.019996*np.tanh(((data["loo_ps_ind_09_bin"] * data["ps_car_12"])- np.tanh(((data["ps_reg_02"] + data["ps_car_12"])/2.0))))
v["229"] = 0.019219*np.tanh(( data["ps_ind_01"] *(( data["loo_ps_ind_17_bin"] * data["loo_ps_car_06_cat"])- np.tanh(data["loo_ps_ind_17_bin"]))))
v["230"] = 0.019996*np.tanh(( data["loo_ps_ind_07_bin"] *(data["ps_car_13"] *(data["loo_ps_car_11_cat"] - np.tanh(2.0)))))
 v["231"] = 0.020000*np.tanh(( data["loo_ps_car_11_cat"] *(( data["ps_ind_14"] * data["ps_ind_15"])* data["ps_car_12"])))
 v["232"] = 0.019816*np.tanh(((np.tanh(data["loo_ps_ind_17_bin"])* data["missing"])*(np.tanh(data["ps_car_15"])- data["loo_ps_car_02_cat"])))
 v["233"] = 0.020000*np.tanh(((( data["loo_ps_car_01_cat"] - data["ps_reg_01"])* data["loo_ps_car_10_cat"])*(data["ps_ind_03"] + data["loo_ps_ind_17_bin"])))
 v["234"] = 0.017378*np.tanh(((data["ps_ind_01"] * data["loo_ps_car_04_cat"])*(data["loo_ps_car_01_cat"] +(data["ps_car_12"] * data["loo_ps_car_04_cat"]))))
v["235"] = 0.020000*np.tanh(( data["ps_reg_03"] *(((( data["ps_reg_03"] + data["loo_ps_ind_05_cat"])/2.0)- data["loo_ps_ind_02_cat"])- data["ps_reg_01"])))
 v["236"] = 0.020000*np.tanh(( data["ps_ind_01"] *(((data["loo_ps_car_09_cat"] + data["loo_ps_ind_04_cat"])/2.0)*(( data["loo_ps_ind_05_cat"] + data["loo_ps_ind_05_cat"])/2.0))))
v["237"] = 0.019996*np.tanh(( data["ps_ind_01"] *(( data["loo_ps_ind_02_cat"] +(data["ps_reg_01"] +(-(data["loo_ps_car_11_cat"])))) /2.0)))
 v["238"] = 0.019941*np.tanh(( -(( data["loo_ps_car_08_cat"] *(data["loo_ps_car_02_cat"] -(( data["loo_ps_car_04_cat"] +(-(data["loo_ps_ind_18_bin"])))/2.0))))))
v["239"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(((data["loo_ps_ind_17_bin"] *(-(np.tanh(data["loo_ps_car_08_cat"])))) + data["ps_reg_02"])/2.0)))
 v["240"] = 0.020000*np.tanh(((np.tanh(( -(data["loo_ps_ind_08_bin"])))+(data["ps_reg_03"] *(data["loo_ps_ind_08_bin"] * data["ps_reg_01"])))/2.0))
v["241"] = 0.019969*np.tanh(((( data["loo_ps_car_02_cat"] + data["ps_car_15"])/2.0)*(( -(data["loo_ps_ind_17_bin"])) - data["loo_ps_car_10_cat"])))
 v["242"] = 0.019371*np.tanh(((data["loo_ps_car_03_cat"] *(data["ps_ind_14"] - data["loo_ps_ind_05_cat"])) *(data["ps_car_11"] + data["ps_car_11"])))
 v["243"] = 0.020000*np.tanh(((( data["loo_ps_car_10_cat"] *(data["loo_ps_ind_17_bin"] * data["loo_ps_ind_04_cat"])) +(-(np.tanh(data["loo_ps_ind_04_cat"])))) /2.0))
v["244"] = 0.020000*np.tanh(( np.tanh(( 19.500000 *(( 0.452381 + data["loo_ps_ind_18_bin"])/2.0)))* data["loo_ps_ind_05_cat"]))
v["245"] = 0.019996*np.tanh(((( data["loo_ps_car_01_cat"] * data["loo_ps_ind_02_cat"])*(data["loo_ps_car_08_cat"] * data["ps_reg_01"])) *(4.34056949615478516)))
 v["246"] = 0.019988*np.tanh(((data["loo_ps_car_01_cat"] + data["loo_ps_ind_16_bin"])*(data["loo_ps_ind_02_cat"] - data["loo_ps_ind_05_cat"])))
 v["247"] = 0.020000*np.tanh(( data["ps_car_14"] *(((data["loo_ps_car_07_cat"] * data["ps_ind_15"])+(( data["ps_car_13"] + data["loo_ps_ind_13_bin"])/2.0)) /2.0)))
 v["248"] = 0.019969*np.tanh(( data["ps_reg_02"] *(( data["ps_ind_15"] + data["ps_ind_14"])*(data["loo_ps_ind_08_bin"] * data["loo_ps_car_08_cat"]))))
v["249"] = 0.019984*np.tanh(( data["loo_ps_ind_02_cat"] *(data["missing"] -(( data["loo_ps_ind_02_cat"] * data["loo_ps_ind_02_cat"])* data["loo_ps_car_08_cat"]))))
v["250"] = 0.020000*np.tanh(((((( data["loo_ps_car_03_cat"] + data["ps_car_15"])/2.0)+ data["loo_ps_ind_06_bin"])/2.0)*(data["ps_reg_02"] * data["ps_car_15"])))
 v["251"] = 0.020000*np.tanh(((data["ps_car_11"] *(( data["loo_ps_car_06_cat"] +(data["ps_reg_02"] * data["loo_ps_ind_12_bin"])) /2.0)) - data["loo_ps_car_10_cat"]))
v["252"] = 0.019453*np.tanh(( data["ps_ind_03"] *(( 0.273684 * data["loo_ps_ind_05_cat"])+(0.020833 - data["ps_car_14"]))))
v["253"] = 0.020000*np.tanh(( data["ps_car_13"] *(( data["ps_car_13"] *(data["loo_ps_ind_12_bin"] * data["ps_ind_15"])) + data["ps_ind_14"])))
 v["254"] = 0.020000*np.tanh(( -(((( data["loo_ps_car_10_cat"] *(data["ps_car_13"] + data["ps_car_13"])) + np.tanh(data["loo_ps_ind_05_cat"])) /2.0))))
v["255"] = 0.019961*np.tanh(((((data["ps_ind_03"] + data["loo_ps_ind_07_bin"])/2.0)* data["ps_ind_14"])-(data["ps_reg_02"] * data["loo_ps_car_10_cat"])))
 v["256"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(( data["loo_ps_car_11_cat"] *(data["loo_ps_ind_04_cat"] - 0.583333)) - data["loo_ps_ind_08_bin"])))
 v["257"] = 0.019664*np.tanh(( data["loo_ps_car_07_cat"] *(data["loo_ps_ind_09_bin"] - data["loo_ps_car_01_cat"])))
 v["258"] = 0.020000*np.tanh(((-(data["loo_ps_ind_17_bin"])) * np.tanh(( data["loo_ps_car_11_cat"] *(data["loo_ps_car_08_cat"] + data["ps_ind_15"])))))
 v["259"] = 0.019644*np.tanh(((data["ps_ind_01"] *(-(data["ps_ind_03"])))*(data["loo_ps_ind_04_cat"] + data["loo_ps_ind_04_cat"])))
 v["260"] = 0.020000*np.tanh(( data["ps_reg_03"] *(-(( data["ps_car_15"] *(data["loo_ps_car_07_cat"] * data["loo_ps_ind_17_bin"]))))))
v["261"] = 0.020000*np.tanh(( data["ps_car_12"] *(( data["ps_car_12"] *(data["ps_ind_15"] * data["loo_ps_ind_04_cat"])) + data["ps_ind_15"])))
 v["262"] = 0.018953*np.tanh(((data["ps_ind_15"] +(data["ps_ind_15"] *(( data["loo_ps_ind_08_bin"] - data["loo_ps_car_04_cat"])- data["loo_ps_car_03_cat"])))/2.0))
v["263"] = 0.020000*np.tanh(( 0.166667 *(((data["ps_car_13"] + data["loo_ps_ind_04_cat"])/2.0)-(data["ps_car_13"] * data["loo_ps_car_03_cat"]))))
v["264"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(( data["loo_ps_ind_09_bin"] +(( data["loo_ps_ind_02_cat"] * data["loo_ps_ind_02_cat"])+ data["loo_ps_ind_10_bin"])) /2.0)))
 v["265"] = 0.019992*np.tanh(( data["ps_ind_14"] *(( data["loo_ps_car_03_cat"] *(data["loo_ps_ind_07_bin"] + data["ps_ind_15"])) * data["loo_ps_car_11_cat"])))
 v["266"] = 0.019988*np.tanh(( np.tanh(np.tanh(data["loo_ps_car_07_cat"])) +(np.tanh(data["ps_ind_01"])*(-(data["ps_ind_14"])))))
 v["267"] = 0.020000*np.tanh(( np.tanh(np.tanh(data["ps_ind_01"])) *(( data["ps_car_14"] +(data["loo_ps_ind_04_cat"] - data["loo_ps_car_01_cat"])) /2.0)))
 v["268"] = 0.020000*np.tanh(((( data["loo_ps_ind_02_cat"] *(data["ps_ind_03"] * data["ps_ind_03"])) - data["loo_ps_ind_02_cat"])- data["loo_ps_ind_02_cat"]))
v["269"] = 0.018969*np.tanh(( data["loo_ps_ind_05_cat"] *(data["loo_ps_car_07_cat"] *(data["ps_reg_02"] + data["ps_car_12"]))))
v["270"] = 0.019996*np.tanh(( data["ps_car_13"] *(data["loo_ps_ind_12_bin"] *(1.135800 +(data["ps_ind_15"] + data["loo_ps_ind_11_bin"])))))
 v["271"] = 0.019996*np.tanh(( -(( data["loo_ps_ind_05_cat"] *(( data["loo_ps_car_07_cat"] *(-(data["loo_ps_car_09_cat"])))+ data["loo_ps_car_07_cat"])))))
 v["272"] = 0.020000*np.tanh(( data["ps_car_11"] *(( -(data["ps_reg_03"])) *(data["loo_ps_ind_05_cat"] * np.tanh(-1.0)))))
 v["273"] = 0.020000*np.tanh(((( data["loo_ps_ind_09_bin"] + data["loo_ps_ind_17_bin"])/2.0)*(( data["loo_ps_ind_18_bin"] +(data["ps_reg_02"] - data["ps_ind_14"])) /2.0)))
 v["274"] = 0.020000*np.tanh(( data["ps_ind_01"] *(((data["ps_ind_01"] * data["loo_ps_car_03_cat"])+ data["loo_ps_ind_02_cat"])/2.0)))
 v["275"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(data["ps_ind_01"] *(data["loo_ps_ind_06_bin"] *(-(data["ps_ind_03"]))))))
v["276"] = 0.019949*np.tanh(((np.tanh(((( data["loo_ps_ind_12_bin"] + data["ps_reg_03"])/2.0)* 19.500000)) +(-(data["ps_reg_03"])))/2.0))
v["277"] = 0.016070*np.tanh(((data["ps_car_15"] + data["loo_ps_car_03_cat"])*(-(( data["ps_reg_03"] + data["loo_ps_ind_05_cat"])))))
 v["278"] = 0.019930*np.tanh(((data["loo_ps_ind_02_cat"] +(( data["loo_ps_car_05_cat"] * data["loo_ps_ind_05_cat"])- data["loo_ps_ind_05_cat"])) /2.0))
v["279"] = 0.017035*np.tanh(((( data["loo_ps_car_09_cat"] * data["ps_reg_03"])+ data["loo_ps_ind_02_cat"])* data["loo_ps_ind_05_cat"]))
v["280"] = 0.019965*np.tanh(((data["ps_reg_01"] + data["loo_ps_ind_07_bin"])*(( data["loo_ps_ind_05_cat"] +(( data["loo_ps_car_11_cat"] + data["loo_ps_car_08_cat"])/2.0)) /2.0)))
 v["281"] = 0.020000*np.tanh(( -(((np.tanh(((data["loo_ps_car_01_cat"] + data["loo_ps_car_05_cat"])/2.0)) +(data["loo_ps_car_10_cat"] * data["ps_car_15"])) /2.0))))
v["282"] = 0.019992*np.tanh(((data["ps_ind_03"] - data["loo_ps_ind_18_bin"])*(((data["ps_ind_03"] + data["ps_car_12"])/2.0)* data["loo_ps_car_02_cat"])))
 v["283"] = 0.019945*np.tanh(( data["loo_ps_ind_04_cat"] *(-(( data["ps_reg_02"] *(data["loo_ps_car_07_cat"] * data["loo_ps_ind_17_bin"]))))))
v["284"] = 0.020000*np.tanh(((-(( 3.642860 +(-(data["loo_ps_car_09_cat"])))))*(data["ps_ind_01"] * data["loo_ps_car_09_cat"])))
 v["285"] = 0.018918*np.tanh(( data["ps_ind_01"] *(data["ps_ind_01"] -(data["ps_ind_01"] * data["ps_ind_01"]))))
v["286"] = 0.018738*np.tanh(((( data["ps_ind_03"] + data["ps_ind_15"])/2.0)-(data["ps_ind_15"] *(data["ps_ind_15"] * data["ps_ind_03"]))))
v["287"] = 0.019957*np.tanh(((data["loo_ps_car_08_cat"] * data["loo_ps_ind_08_bin"])*(( data["loo_ps_car_07_cat"] + data["missing"])/2.0)))
 v["288"] = 0.019598*np.tanh(((data["loo_ps_ind_09_bin"] *(( data["ps_ind_01"] +(-(data["loo_ps_car_05_cat"])))/2.0)) + data["loo_ps_ind_13_bin"]))
v["289"] = 0.020000*np.tanh(((( data["loo_ps_car_01_cat"] * data["ps_ind_15"])+ data["ps_car_11"])* data["loo_ps_ind_12_bin"]))
v["290"] = 0.020000*np.tanh(((( data["loo_ps_ind_02_cat"] -(data["ps_car_11"] * data["loo_ps_car_09_cat"])) * data["loo_ps_ind_17_bin"])* data["loo_ps_car_10_cat"]))
v["291"] = 0.019301*np.tanh(( data["loo_ps_car_04_cat"] *(( np.tanh(data["loo_ps_car_04_cat"])- data["ps_ind_03"])* data["ps_ind_03"])))
 v["292"] = 0.020000*np.tanh(((data["ps_reg_03"] - data["ps_car_11"])*(( np.tanh(data["loo_ps_car_04_cat"])+(-(data["ps_car_14"])))/2.0)))
 v["293"] = 0.019086*np.tanh(((( data["ps_ind_03"] * data["loo_ps_ind_12_bin"])+(( data["loo_ps_ind_12_bin"] - data["loo_ps_car_06_cat"])* data["ps_reg_03"])) /2.0))
v["294"] = 0.020000*np.tanh(( data["loo_ps_ind_12_bin"] -(data["loo_ps_ind_18_bin"] *(data["loo_ps_ind_04_cat"] *(-(data["ps_reg_03"]))))))
v["295"] = 0.019988*np.tanh(((((data["ps_reg_03"] * data["ps_car_12"])+ data["loo_ps_ind_02_cat"])/2.0)* np.tanh(data["loo_ps_car_04_cat"])))
 v["296"] = 0.019898*np.tanh(( data["loo_ps_car_07_cat"] *(-(((( data["ps_car_11"] *(-(data["loo_ps_car_08_cat"])))+ data["loo_ps_car_09_cat"])/2.0)))))
 v["297"] = 0.019973*np.tanh(((data["loo_ps_ind_02_cat"] *(data["loo_ps_ind_16_bin"] +(-(data["loo_ps_car_05_cat"])))) *(-(data["loo_ps_car_08_cat"]))))
v["298"] = 0.019980*np.tanh(((( data["loo_ps_ind_18_bin"] *(data["loo_ps_ind_04_cat"] * data["loo_ps_ind_16_bin"])) - data["ps_car_14"])* data["ps_ind_14"]))
v["299"] = 0.016964*np.tanh(((( -(0.347826)) + np.tanh(( data["loo_ps_car_06_cat"] - data["ps_reg_01"])))/2.0))
v["300"] = 0.020000*np.tanh(((data["ps_ind_15"] * data["ps_car_15"])*(( data["loo_ps_ind_12_bin"] +(-(data["ps_car_15"])))/2.0)))
 v["301"] = 0.019957*np.tanh(((data["ps_car_14"] * data["loo_ps_ind_04_cat"])*(data["ps_ind_01"] +(data["ps_car_14"] * data["loo_ps_car_08_cat"]))))
v["302"] = 0.020000*np.tanh(( data["ps_ind_14"] *(data["ps_car_11"] *(data["ps_car_12"] +(data["ps_ind_03"] * data["ps_car_12"])))))
 v["303"] = 0.020000*np.tanh(( data["ps_reg_01"] *(data["loo_ps_car_01_cat"] *(( data["loo_ps_car_01_cat"] +(data["ps_ind_03"] * data["ps_reg_02"])) /2.0))))
v["304"] = 0.019594*np.tanh(((data["loo_ps_ind_04_cat"] * data["loo_ps_ind_02_cat"])*(data["loo_ps_car_06_cat"] *(0.347826 + 2.800000))))
v["305"] = 0.019992*np.tanh(( data["ps_reg_01"] *(( data["loo_ps_car_02_cat"] - data["loo_ps_car_04_cat"])* data["loo_ps_ind_05_cat"])))
 v["306"] = 0.020000*np.tanh(np.tanh(((((data["loo_ps_ind_09_bin"] * data["loo_ps_ind_05_cat"])+ data["ps_ind_03"])/2.0)*(-(data["ps_reg_01"])))))
 v["307"] = 0.018308*np.tanh(( -(( 19.500000 * np.tanh(( -1.0 -(data["loo_ps_ind_11_bin"] * 19.500000)))))))
 v["308"] = 0.019754*np.tanh(((1.0 + data["ps_reg_02"])*(( data["ps_reg_02"] - 3.0)* 3.0)))
 v["309"] = 0.019265*np.tanh(( data["loo_ps_ind_04_cat"] *(( data["ps_ind_01"] *(data["ps_reg_01"] * data["ps_ind_01"])) * data["ps_ind_01"])))
 v["310"] = 0.019879*np.tanh(((( data["ps_reg_03"] + data["ps_ind_03"])/2.0)* np.tanh(( data["ps_reg_03"] * data["ps_ind_03"]))))
v["311"] = 0.020000*np.tanh(((data["ps_reg_02"] *(data["loo_ps_ind_11_bin"] -(data["ps_car_14"] * data["loo_ps_car_04_cat"])))* data["ps_reg_01"]))
v["312"] = 0.019965*np.tanh(( data["ps_reg_03"] *(( data["ps_ind_15"] +(( data["ps_ind_15"] * data["loo_ps_ind_09_bin"])- data["loo_ps_ind_08_bin"])) /2.0)))
 v["313"] = 0.020000*np.tanh(( data["loo_ps_ind_06_bin"] *(( data["loo_ps_ind_02_cat"] +(data["ps_car_11"] * data["loo_ps_car_06_cat"])) /2.0)))
 v["314"] = 0.020000*np.tanh(( data["loo_ps_ind_05_cat"] *(data["loo_ps_ind_11_bin"] -(data["loo_ps_ind_04_cat"] * data["ps_car_11"]))))
v["315"] = 0.019461*np.tanh(( data["loo_ps_car_03_cat"] *(data["loo_ps_ind_05_cat"] *(data["loo_ps_car_02_cat"] + data["loo_ps_ind_04_cat"]))))
v["316"] = 0.014366*np.tanh(np.tanh(np.tanh(( data["ps_reg_01"] -(( data["ps_ind_03"] +(( data["ps_ind_14"] + data["loo_ps_car_10_cat"])/2.0)) /2.0)))))
 v["317"] = 0.019996*np.tanh(( data["ps_car_12"] *(( data["loo_ps_ind_12_bin"] +(data["ps_car_11"] *(data["ps_ind_15"] + data["ps_car_11"])))/2.0)))
 v["318"] = 0.020000*np.tanh(np.tanh(( data["ps_car_14"] *(( -(np.tanh(data["ps_car_14"])))+(-(data["ps_reg_03"]))))))
v["319"] = 0.015050*np.tanh(( -(( np.tanh(data["loo_ps_car_04_cat"])*(data["ps_car_15"] *(data["loo_ps_ind_18_bin"] - data["loo_ps_ind_06_bin"]))))))
v["320"] = 0.020000*np.tanh(( data["ps_car_13"] *(((data["loo_ps_car_04_cat"] *(data["ps_car_14"] - data["ps_ind_03"])) + data["ps_ind_03"])/2.0)))
 v["321"] = 0.020000*np.tanh(( -(( data["ps_car_14"] +(( 0.347826 - data["ps_car_14"])* data["ps_car_15"])))))
 v["322"] = 0.019977*np.tanh(((0.166667 +(data["ps_ind_14"] *(( data["ps_reg_03"] - data["loo_ps_ind_08_bin"])- data["loo_ps_ind_17_bin"])))/2.0))
v["323"] = 0.020000*np.tanh(( data["missing"] *(-(( data["loo_ps_car_09_cat"] *(( data["ps_car_12"] + data["loo_ps_ind_18_bin"])/2.0))))))
v["324"] = 0.018195*np.tanh(((( data["loo_ps_ind_09_bin"] +(-(np.tanh(data["loo_ps_ind_05_cat"])))) /2.0)*(data["loo_ps_ind_18_bin"] + data["loo_ps_car_07_cat"])))
 v["325"] = 0.019359*np.tanh(( -(( 19.500000 *(( 0.485294 + np.tanh(( data["loo_ps_ind_11_bin"] * 19.500000)))/2.0)))))
 v["326"] = 0.019992*np.tanh(( -3.0 -(( -(( data["ps_ind_03"] * data["ps_ind_03"])))+ data["ps_ind_03"])))
 v["327"] = 0.020000*np.tanh(( np.tanh(( data["ps_reg_01"] *(data["ps_car_14"] *(-(data["loo_ps_ind_02_cat"])))))- data["loo_ps_ind_02_cat"]))
v["328"] = 0.019992*np.tanh(( data["loo_ps_ind_04_cat"] *(( data["ps_ind_03"] + data["loo_ps_ind_04_cat"])*(-(data["loo_ps_car_08_cat"])))))
 v["329"] = 0.020000*np.tanh(( data["ps_car_11"] *(( data["loo_ps_ind_02_cat"] +(( data["loo_ps_ind_07_bin"] +(data["loo_ps_car_07_cat"] * data["missing"])) /2.0)) /2.0)))
 v["330"] = 0.019996*np.tanh(((( data["loo_ps_car_02_cat"] -(data["loo_ps_ind_06_bin"] - data["loo_ps_car_02_cat"])) * data["loo_ps_car_09_cat"])* data["loo_ps_ind_02_cat"]))
v["331"] = 0.018343*np.tanh(((( data["loo_ps_car_07_cat"] +(data["ps_reg_03"] + np.tanh(data["loo_ps_car_07_cat"])))/2.0)*(-(data["missing"]))))
v["332"] = 0.019750*np.tanh(( -(( data["loo_ps_ind_02_cat"] *(data["loo_ps_ind_18_bin"] *(data["ps_car_14"] * data["loo_ps_car_04_cat"]))))))
v["333"] = 0.019949*np.tanh(((data["loo_ps_ind_05_cat"] *(-(data["loo_ps_car_06_cat"])))*(data["loo_ps_ind_05_cat"] * data["loo_ps_ind_04_cat"])))
 v["334"] = 0.020000*np.tanh(( data["loo_ps_car_06_cat"] *(( 2.800000 + data["ps_car_14"])*(data["loo_ps_ind_13_bin"] * data["loo_ps_car_04_cat"]))))
v["335"] = 0.020000*np.tanh(np.tanh(( data["ps_ind_03"] * np.tanh(np.tanh(( data["ps_reg_02"] *(-(data["ps_ind_15"]))))))))
v["336"] = 0.020000*np.tanh(( data["loo_ps_car_10_cat"] *(( data["loo_ps_ind_11_bin"] + data["loo_ps_ind_18_bin"])*(data["ps_reg_02"] + data["ps_reg_02"]))))
v["337"] = 0.020000*np.tanh(np.tanh(np.tanh(( data["ps_ind_03"] *(( data["ps_ind_03"] + data["ps_car_11"])+ data["ps_car_11"])))))
 v["338"] = 0.019984*np.tanh(((data["loo_ps_ind_05_cat"] *(data["loo_ps_ind_11_bin"] -(data["ps_car_11"] * data["loo_ps_ind_06_bin"])))* data["loo_ps_car_01_cat"]))
v["339"] = 0.020000*np.tanh(( data["ps_car_15"] *(data["loo_ps_ind_12_bin"] *(data["loo_ps_car_08_cat"] + data["loo_ps_ind_07_bin"]))))
v["340"] = 0.019953*np.tanh(( data["ps_ind_15"] *(data["loo_ps_ind_02_cat"] *(0.600000 -(data["loo_ps_ind_10_bin"] - data["ps_reg_03"])))))
 v["341"] = 0.017914*np.tanh(((data["loo_ps_car_03_cat"] -(data["ps_car_13"] + data["loo_ps_ind_18_bin"])) *(data["loo_ps_car_03_cat"] * 0.273684)))
 v["342"] = 0.020000*np.tanh(( data["loo_ps_car_10_cat"] *(-3.0 +(data["ps_car_14"] *(data["ps_car_15"] - data["loo_ps_car_04_cat"])))))
 v["343"] = 0.020000*np.tanh(( data["loo_ps_car_09_cat"] *(((data["ps_car_11"] * data["loo_ps_car_09_cat"])+(data["loo_ps_car_02_cat"] - data["loo_ps_ind_04_cat"])) /2.0)))
 v["344"] = 0.019973*np.tanh(((data["ps_car_13"] *(data["ps_ind_14"] - data["ps_reg_02"])) * data["ps_ind_15"]))
v["345"] = 0.020000*np.tanh(((data["loo_ps_car_09_cat"] *(( 0.965909 - data["ps_reg_03"])- data["ps_reg_03"])) * data["loo_ps_ind_08_bin"]))
v["346"] = 0.019973*np.tanh(((data["ps_ind_01"] *(np.tanh(data["loo_ps_car_02_cat"])+ data["loo_ps_ind_11_bin"])) *(-(data["ps_car_15"]))))
v["347"] = 0.020000*np.tanh(( data["loo_ps_ind_09_bin"] *(((-(data["loo_ps_car_08_cat"])) * data["loo_ps_car_03_cat"])* data["ps_ind_03"])))
 v["348"] = 0.018535*np.tanh(( data["loo_ps_ind_04_cat"] *(data["loo_ps_car_04_cat"] *(data["ps_ind_15"] -(-(data["loo_ps_car_01_cat"]))))))
v["349"] = 0.020000*np.tanh(( data["loo_ps_car_07_cat"] *(((( data["loo_ps_ind_10_bin"] + data["loo_ps_car_08_cat"])/2.0)+(-(data["loo_ps_ind_12_bin"])))/2.0)))
 v["350"] = 0.019996*np.tanh(((data["loo_ps_car_10_cat"] *(data["loo_ps_ind_13_bin"] - data["ps_reg_02"])) *(data["loo_ps_ind_17_bin"] + data["ps_ind_03"])))
 v["351"] = 0.020000*np.tanh(( data["loo_ps_ind_06_bin"] *(data["ps_reg_01"] *(( data["missing"] +(data["loo_ps_car_07_cat"] - data["loo_ps_ind_05_cat"])) /2.0))))
v["352"] = 0.020000*np.tanh(( data["ps_car_12"] *(data["ps_car_12"] *(( -(np.tanh(data["loo_ps_car_07_cat"])))* data["ps_reg_02"]))))
v["353"] = 0.020000*np.tanh(((( -(( data["ps_ind_01"] *(data["ps_ind_03"] * data["loo_ps_ind_02_cat"])))) + np.tanh(data["loo_ps_car_08_cat"])) /2.0))
v["354"] = 0.016128*np.tanh(( data["ps_ind_15"] *(data["loo_ps_car_11_cat"] *(((data["ps_ind_15"] * data["loo_ps_car_11_cat"])+ 1.871790)/2.0))))
v["355"] = 0.019961*np.tanh(( data["loo_ps_ind_06_bin"] *(data["loo_ps_ind_12_bin"] *(data["loo_ps_ind_11_bin"] +(( data["ps_ind_15"] + data["loo_ps_car_11_cat"])/2.0)))))
 v["356"] = 0.019836*np.tanh(((np.tanh(data["ps_ind_15"])+(data["loo_ps_ind_02_cat"] *(data["ps_ind_15"] *(-(data["loo_ps_ind_02_cat"])))))/2.0))
v["357"] = 0.019840*np.tanh(((data["ps_car_15"] *(data["loo_ps_ind_17_bin"] - 0.093750)) * data["ps_car_15"]))
v["358"] = 0.020000*np.tanh(( -(( data["loo_ps_car_09_cat"] *(( data["loo_ps_car_01_cat"] +(data["ps_reg_02"] * data["loo_ps_car_09_cat"])) /2.0)))))
 v["359"] = 0.020000*np.tanh(( -(((data["loo_ps_ind_17_bin"] + data["loo_ps_ind_17_bin"])*(( np.tanh(data["ps_ind_01"])+ 0.452381)/2.0)))))
 v["360"] = 0.020000*np.tanh(( data["loo_ps_ind_08_bin"] *(data["ps_car_14"] *(data["loo_ps_ind_02_cat"] - np.tanh(data["loo_ps_car_04_cat"])))))
 v["361"] = 0.019996*np.tanh(((( data["loo_ps_ind_11_bin"] +(data["loo_ps_ind_08_bin"] *(data["ps_ind_01"] * data["ps_car_11"])))/2.0)* data["ps_car_11"]))
v["362"] = 0.020000*np.tanh(((8.47791767120361328)*(data["loo_ps_ind_10_bin"] *(data["ps_car_11"] +(data["ps_car_14"] * data["loo_ps_car_08_cat"])))))
 v["363"] = 0.019152*np.tanh(((( data["loo_ps_car_08_cat"] +(data["loo_ps_car_08_cat"] *(-(data["ps_ind_03"])))) /2.0)* data["ps_ind_03"]))
v["364"] = 0.020000*np.tanh(( data["loo_ps_ind_16_bin"] *(data["ps_ind_14"] *(( data["ps_car_12"] +(data["ps_reg_03"] * data["loo_ps_car_01_cat"])) /2.0))))
v["365"] = 0.019996*np.tanh(((( data["ps_car_15"] *(data["ps_ind_01"] * data["ps_reg_02"])) +(data["loo_ps_ind_02_cat"] * data["ps_reg_02"])) /2.0))
v["366"] = 0.020000*np.tanh(( data["loo_ps_ind_12_bin"] *(( data["loo_ps_ind_11_bin"] - data["loo_ps_car_10_cat"])-(data["loo_ps_ind_17_bin"] * data["loo_ps_ind_07_bin"]))))
v["367"] = 0.019996*np.tanh(( -(((data["loo_ps_ind_17_bin"] * data["loo_ps_car_02_cat"])*(0.347826 - data["ps_car_15"])))))
 v["368"] = 0.020000*np.tanh(( data["loo_ps_ind_02_cat"] *(( data["ps_reg_03"] *(data["loo_ps_car_04_cat"] * data["loo_ps_car_01_cat"])) * data["loo_ps_car_08_cat"])))
 v["369"] = 0.020000*np.tanh(((( data["ps_reg_02"] + data["ps_ind_15"])* data["loo_ps_ind_12_bin"])*(data["ps_ind_03"] + data["ps_ind_03"])))
 v["370"] = 0.020000*np.tanh(( data["loo_ps_ind_16_bin"] *(data["ps_car_12"] *(data["loo_ps_ind_02_cat"] *(0.485294 - data["loo_ps_car_08_cat"])))))
 v["371"] = 0.020000*np.tanh(((data["loo_ps_ind_12_bin"] *(-(data["ps_reg_01"])))-(data["loo_ps_ind_04_cat"] * np.tanh(data["ps_ind_15"]))))
v["372"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] *(((data["loo_ps_car_02_cat"] * data["loo_ps_ind_04_cat"])+ data["loo_ps_ind_10_bin"])/2.0)) * data["loo_ps_car_03_cat"]))
v["373"] = 0.020000*np.tanh(((data["ps_ind_14"] * data["loo_ps_car_11_cat"])* np.tanh(( data["ps_ind_03"] + data["ps_ind_15"]))))
v["374"] = 0.019984*np.tanh(( data["ps_car_12"] *(( data["loo_ps_ind_12_bin"] *(1.526320 - data["ps_car_13"])) + data["loo_ps_ind_12_bin"])))
 v["375"] = 0.019684*np.tanh(( data["loo_ps_ind_08_bin"] *(((( data["loo_ps_ind_16_bin"] + np.tanh(data["ps_reg_02"])) /2.0)+ 0.100000)/2.0)))
 v["376"] = 0.018172*np.tanh(((( data["ps_car_11"] + 1.135800)/2.0)*(data["ps_reg_03"] *(data["ps_ind_03"] + data["loo_ps_ind_12_bin"]))))
v["377"] = 0.020000*np.tanh(((data["ps_car_11"] *(( data["loo_ps_ind_10_bin"] + data["ps_car_11"])+ 1.526320)) * data["loo_ps_car_10_cat"]))
v["378"] = 0.020000*np.tanh(( data["loo_ps_ind_12_bin"] *(( data["ps_ind_03"] +(( data["ps_ind_15"] +(-(data["ps_car_14"])))/2.0)) /2.0)))
 v["379"] = 0.020000*np.tanh(( data["ps_car_11"] *(((data["loo_ps_car_09_cat"] +(data["ps_ind_01"] * data["loo_ps_ind_11_bin"])) /2.0)* data["ps_ind_01"])))
 v["380"] = 0.019898*np.tanh(( data["loo_ps_ind_12_bin"] *(data["ps_ind_03"] -(data["ps_car_11"] +(( -2.0 + data["loo_ps_car_08_cat"])/2.0)))))
 v["381"] = 0.020000*np.tanh(((( data["ps_car_11"] * data["loo_ps_ind_18_bin"])* data["ps_car_11"])* data["ps_ind_14"]))
v["382"] = 0.020000*np.tanh(( data["loo_ps_ind_04_cat"] *(data["ps_ind_03"] *(( data["ps_ind_03"] * data["ps_car_12"])- data["ps_ind_03"]))))
v["383"] = 0.019980*np.tanh(( data["loo_ps_ind_02_cat"] *(((data["ps_car_11"] + data["ps_car_15"])/2.0)+(data["ps_car_15"] * data["ps_car_11"]))))
v["384"] = 0.019836*np.tanh(((data["loo_ps_car_06_cat"] * data["loo_ps_ind_04_cat"])*(( data["loo_ps_ind_04_cat"] * data["ps_ind_14"])+ data["loo_ps_car_08_cat"])))
 v["385"] = 0.019965*np.tanh(((data["ps_car_13"] + data["ps_ind_15"])*(data["ps_ind_03"] *(data["ps_reg_02"] + data["ps_car_15"]))))
v["386"] = 0.019508*np.tanh(( data["ps_ind_15"] *(data["ps_reg_01"] *(( data["loo_ps_car_06_cat"] * data["loo_ps_car_04_cat"])+ data["loo_ps_ind_13_bin"]))))
v["387"] = 0.015862*np.tanh(((( data["ps_reg_02"] + data["loo_ps_car_08_cat"])/2.0)*(data["ps_car_13"] *(data["ps_car_12"] - 2.0))))
v["388"] = 0.020000*np.tanh(( data["ps_car_13"] *(0.100000 -(( data["loo_ps_car_10_cat"] * data["ps_ind_01"])* data["ps_ind_01"]))))
v["389"] = 0.019992*np.tanh(( data["ps_car_13"] *(data["loo_ps_ind_12_bin"] *(data["ps_reg_01"] + data["ps_ind_15"]))))
v["390"] = 0.015315*np.tanh(((np.tanh(np.tanh(( data["loo_ps_ind_07_bin"] + data["loo_ps_car_06_cat"])))+ np.tanh(data["loo_ps_car_08_cat"])) /2.0))
v["391"] = 0.020000*np.tanh(( data["ps_car_15"] *(0.452381 -(data["loo_ps_car_08_cat"] *(( data["loo_ps_ind_11_bin"] + data["ps_car_15"])/2.0)))))
 v["392"] = 0.020000*np.tanh(((data["loo_ps_ind_05_cat"] + data["loo_ps_ind_06_bin"])*(( data["loo_ps_car_10_cat"] - data["loo_ps_car_02_cat"])* data["loo_ps_car_10_cat"])))
 v["393"] = 0.015452*np.tanh(( data["loo_ps_ind_06_bin"] *(( data["loo_ps_car_08_cat"] +(data["loo_ps_ind_09_bin"] * data["loo_ps_car_09_cat"])) /2.0)))
 v["394"] = 0.019977*np.tanh(( data["loo_ps_ind_17_bin"] *(( data["loo_ps_ind_08_bin"] * data["ps_car_15"])*(0.485294 - data["loo_ps_ind_02_cat"]))))
v["395"] = 0.019977*np.tanh(( data["loo_ps_ind_04_cat"] *(( data["ps_reg_02"] +(( data["loo_ps_ind_04_cat"] - data["ps_ind_01"])- data["loo_ps_car_09_cat"])) /2.0)))
 v["396"] = 0.019980*np.tanh(( data["ps_reg_01"] *(data["loo_ps_car_10_cat"] *(-(( data["loo_ps_ind_12_bin"] + data["ps_reg_02"]))))))
v["397"] = 0.020000*np.tanh(((data["ps_car_15"] *(( data["loo_ps_ind_16_bin"] + data["loo_ps_car_10_cat"])/2.0)) *(data["ps_car_15"] - data["loo_ps_ind_16_bin"])))
 v["398"] = 0.020000*np.tanh(((( -(( data["loo_ps_ind_02_cat"] *(data["ps_car_14"] * data["loo_ps_ind_07_bin"])))) + np.tanh(data["ps_car_15"])) /2.0))
v["399"] = 0.014948*np.tanh(( data["ps_reg_02"] *(data["loo_ps_car_08_cat"] *(-(data["ps_ind_03"])))))
 v["400"] = 0.016214*np.tanh(( data["loo_ps_car_04_cat"] * np.tanh(( data["loo_ps_car_11_cat"] -(data["loo_ps_ind_07_bin"] + 1.526320)))))
 v["0"] = -3.274750
return v 
<groupby>
class TrainGlobalConfig:

 num_workers = 0
batch_size = 16
n_epochs = 3
lr = 0.5 * 1e-5
fold_number = 0
verbose = True
verbose_step = 5
step_scheduler = False
validation_scheduler = True
SchedulerClass = torch.optim.lr_scheduler.ReduceLROnPlateau
scheduler_params = dict(
 mode='max',
factor=0.7,
patience=0,
verbose=False,
threshold=0.0001,
threshold_mode='abs',
cooldown=0,
min_lr=1e-8,
eps=1e-08 
)
 criterion = LabelSmoothing()
def GPAri(data):
return(GPI(data)+GPII(data)) /2.
 def ProjectOnMean(data1, data2, columnName):
grpOutcomes = data1.groupby(list([columnName])) ['target'].mean().reset_index()
grpCount = data1.groupby(list([columnName])) ['target'].count().reset_index()
grpOutcomes['cnt'] = grpCount.target
grpOutcomes.drop('cnt', inplace=True, axis=1)
 outcomes = data2['target'].values
x = pd.merge(data2[[columnName, 'target']], grpOutcomes,
suffixes=('x_', ''),
how='left',
on=list([columnName]),
left_index=True)['target']
return x.values<define_variables>
def _mp_fn(rank, flags):
device = xm.xla_device()
net.to(device)
 train_sampler = DistributedSamplerWrapper(
 sampler=BalanceClassSampler(labels=train_dataset.get_labels() , mode="downsampling"),
num_replicas=xm.xrt_world_size() ,
rank=xm.get_ordinal() ,
shuffle=True 
)
 train_loader = torch.utils.data.DataLoader(
 train_dataset,
batch_size=TrainGlobalConfig.batch_size,
sampler=train_sampler,
pin_memory=False,
drop_last=True,
num_workers=TrainGlobalConfig.num_workers, 
)
 validation_sampler = torch.utils.data.distributed.DistributedSampler(
 validation_dataset,
num_replicas=xm.xrt_world_size() ,
rank=xm.get_ordinal() ,
shuffle=False 
)
 validation_loader = torch.utils.data.DataLoader(
 validation_dataset,
batch_size=TrainGlobalConfig.batch_size,
sampler=validation_sampler,
pin_memory=False,
drop_last=False,
num_workers=TrainGlobalConfig.num_workers 
)
 validation_tune_sampler = torch.utils.data.distributed.DistributedSampler(
 validation_tune_dataset,
num_replicas=xm.xrt_world_size() ,
rank=xm.get_ordinal() ,
shuffle=True 
)
 validation_tune_loader = torch.utils.data.DataLoader(
 validation_tune_dataset,
batch_size=TrainGlobalConfig.batch_size,
sampler=validation_tune_sampler,
pin_memory=False,
drop_last=False,
num_workers=TrainGlobalConfig.num_workers 
)
 test_sampler = torch.utils.data.distributed.DistributedSampler(
 test_dataset,
num_replicas=xm.xrt_world_size() ,
rank=xm.get_ordinal() ,
shuffle=False 
)
 test_loader = torch.utils.data.DataLoader(
 test_dataset,
batch_size=TrainGlobalConfig.batch_size,
sampler=test_sampler,
pin_memory=False,
drop_last=False,
num_workers=TrainGlobalConfig.num_workers 
)
 if rank == 0:
time.sleep(1)
 fitter = TPUFitter(model=net, device=device, config=TrainGlobalConfig)
 fitter.fit(train_loader, validation_loader)
 fitter.run_tuning_and_inference(test_loader, validation_tune_loader )
def GetData(strdirectory):
highcardinality = ['ps_car_02_cat',
'ps_car_09_cat',
'ps_ind_04_cat',
'ps_ind_05_cat',
'ps_car_03_cat',
'ps_ind_08_bin',
'ps_car_05_cat',
'ps_car_08_cat',
'ps_ind_06_bin',
'ps_ind_07_bin',
'ps_ind_12_bin',
'ps_ind_18_bin',
'ps_ind_17_bin',
'ps_car_07_cat',
'ps_car_11_cat',
'ps_ind_09_bin',
'ps_car_10_cat',
'ps_car_04_cat',
'ps_car_01_cat',
'ps_ind_02_cat',
'ps_ind_10_bin',
'ps_ind_11_bin',
'ps_car_06_cat',
'ps_ind_13_bin',
'ps_ind_16_bin']
train = pd.read_csv(strdirectory+'train.csv')
 test = pd.read_csv(strdirectory+'test.csv')
 train['missing'] =(train==-1 ).sum(axis=1 ).astype(float)
 test['missing'] =(test==-1 ).sum(axis=1 ).astype(float)
 unwanted = train.columns[train.columns.str.startswith('ps_calc_')]
train.drop(unwanted,inplace=True,axis=1)
 test.drop(unwanted,inplace=True,axis=1)
 ids = train['id']
test['target'] = np.nan
feats = list(set(train.columns ).difference(set(['id','target'])))
 feats = list(['id'])+feats +list(['target'])
 train = train[feats]
test = test[feats]
blindloodata = None
blinddataids = None
folds = N_FOLDS
kf = StratifiedKFold(n_splits=folds,shuffle=True,random_state=42)
 for i,(train_index, test_index)in enumerate(kf.split(range(train.shape[0]),train.target)) :
print('Fold:',i)
 blindtrain = train.loc[test_index].copy()
blindids = ids[test_index].copy()
vistrain = train.loc[train_index].copy()
for c in highcardinality:
blindtrain.insert(1,'loo_'+c, ProjectOnMean(vistrain,
blindtrain,c))
if(blindloodata is None):
blindloodata = blindtrain.copy()
blinddataids = blindids.copy()
else:
blindloodata = pd.concat([blindloodata,blindtrain])
 blinddataids = pd.concat([blinddataids,blindids])
 for c in highcardinality:
test.insert(1,'loo_'+c, ProjectOnMean(train,
test,c))
test.drop(highcardinality,inplace=True,axis=1)
 train = blindloodata
train.drop(highcardinality,inplace=True,axis=1)
 train = train.fillna(train.mean())
 test = test.fillna(train.mean())
 print('Scale values')
 ss = StandardScaler()
features = train.columns[1:-1]
ss.fit(pd.concat([train[features],test[features]]))
train[features] = ss.transform(train[features])
 test[features] = ss.transform(test[features])
 train[features] = np.round(train[features], 6)
 test[features] = np.round(test[features], 6)
 return train, test, blinddataids<train_model>
submission['target'] = submission['target'].apply(lambda x: round(x))
<prepare_x_and_y><EOS> 
submission.to_csv('submission.csv' )