house_prices.py 文件源码

def drop_variable(self, df):
        # if HousePrices._is_one_hot_encoder:
            # Drop all categorical feature helping columns ('Num')
            # Todo: is it defined when importing data set? _feature_names_num
            # for feature_name in HousePrices._feature_names_num:
            #     df = df.drop([feature_name], axis=1)

        # is_with_feature_agglomeration = 0
        # if is_with_feature_agglomeration:
        #     print(df.shape)
        #     df = HousePrices.feature_agglomeration(df)
        #     print(df.shape)

        # df = df.drop(['Fireplaces'], axis=1)
        df = df.drop(['Id'], axis=1)

        if not any(tuple(df.columns == 'SalePrice')):
            # All feature var names occuring in test data is assigned the public varaible df_test_all_feature_var_names.
            self.df_test_all_feature_var_names = df.columns
        return df