feature selection

tele_class = tele['label'].values

pd.isnull(tele).any()

from sklearn.model_selection import train_test_split

# from sklearn.cross_validation import train_test_split
training_indices, validation_indices = training_indices, testing_indices = train_test_split(tele.index,
                                                                                            stratify = tele_class,
                                                                                            train_size=0.75, test_size=0.25)
training_indices.size, validation_indices.size


from tpot import TPOTClassifier
from tpot import TPOTRegressor

tpot = TPOTClassifier(generations=5, verbosity=2)

tpot.fit(tele.drop('label',axis=1).loc[training_indices].values,
         tele.loc[training_indices,'label'].values)