def __init__(self, pipeline_): train = pd.read_csv('data/train.csv', index_col=0) test = pd.read_csv('data/test.csv', index_col=0) add_features = AddFeatures(train, test) add_features.add_bmi_sist_dist_map() add_features.add_f_score() add_features.add_ap_features() add_features.del_features() train = add_features.train test = add_features.test self.Y = train['cardio'].values train.drop('cardio', axis=1, inplace=True) self.X = train self.test = test self.pipeline = pipeline_ self.model = None self.kf = None self.results = pd.DataFrame()
from FEATURES import AddFeatures from mlxtend.classifier import EnsembleVoteClassifier pd.set_option('display.max_columns', 16) pd.set_option('display.width', 1000) plt.style.use('ggplot') warnings.filterwarnings('ignore') train = pd.read_csv('data/train.csv', index_col=0) test = pd.read_csv('data/test.csv', index_col=0) add_features = AddFeatures(train, test) add_features.add_bmi_sist_dist_map() add_features.add_f_score() add_features.add_ap_features() add_features.del_features() train = add_features.train test = add_features.test Y = train['cardio'].values train.drop('cardio', axis=1, inplace=True) X = train best_columns_first = [ 'gender', 'height', 'ap_hi', 'ap_lo', 'smoke', 'alco', 'active', 'age_y', 'ch_1', 'ch_2', 'ch_3', 'gl_1', 'gl_2', 'gl_3', 'bmi', 'sist_formula', 'map', 'F_score', 'ap_log' ]