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'
]