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