def load_test(test_data_path, date, lgbm=True):
dataLoader = DataPrepare.DataLoader(val_size=0, lgbm=lgbm)
dataLoader.load_from_dir(path_data=[test_data_path],
path_real_churn=path_real_churn,
dates=date,
test=True)
X_test = dataLoader.test_data
if lgbm:
X_test_ohe = dataLoader.test_data_ohe
return X_test, X_test_ohe
else:
return X_test, None
def load_data_for_models(val_size=0.2, lgbm=True):
dataLoader = DataPrepare.DataLoader(val_size, lgbm)
dataLoader.load_from_dir(path_data=path_data,
path_real_churn=path_real_churn,
dates=dates)
X_train = dataLoader.all_train_X
y_train = dataLoader.all_train_y
X_val = dataLoader.all_val_X
y_val = dataLoader.all_val_y
print(y_train.value_counts(normalize=True))
if lgbm:
X_train_ohe = dataLoader.all_train_X_ohe
X_val_ohe = dataLoader.all_val_X_ohe
return X_train, y_train, X_val, y_val, X_train_ohe, X_val_ohe
else:
return X_train, y_train, X_val, y_val, None
