def genetic():
    X_train = pd.read_csv(PATH+'train/FINAL_EXTRA.csv')
    X_test = pd.read_csv(PATH+'test/FINAL_EXTRA.csv')
    y = X_train['TARGET'].as_matrix()
    del X_train['ID']
    del X_train['TARGET']
    del X_test['ID']
    Xt = X_train.as_matrix()
    del X_train
    Xp = X_test.as_matrix()
    del X_test
    gp = SymbolicTransformer(generations=20, population_size=2000,
                         hall_of_fame=100, n_components=40,
                         parsimony_coefficient=0.0005,
                         max_samples=0.9, verbose=1,
                         random_state=0, n_jobs=1)
    gp.fit(Xt,y)
    gp_features_train = gp.transform(Xt)
    gp_features_test = gp.transform(Xp)
    pd.DataFrame(gp_features_train).to_csv(PATH+'train/GE_EXTRA.csv',index=False)
    pd.DataFrame(gp_features_test).to_csv(PATH+'test/GE_EXTRA.csv',index=False)
    del gp_features_train
    del gp_features_test