test_one_hot_encoder.py 文件源码

def test_conversion_many_columns(self):
        scikit_model = OneHotEncoder()
        scikit_model.fit(self.scikit_data_multiple_cols)
        spec = sklearn.convert(scikit_model, ['feature_1', 'feature_2'], 'out').get_spec()

        test_data = [{'feature_1': row[0], 'feature_2': row[1]} for row in self.scikit_data_multiple_cols]
        scikit_output = [{'out': row} for row in scikit_model.transform(self.scikit_data_multiple_cols).toarray()]
        metrics = evaluate_transformer(spec, test_data, scikit_output)

        self.assertIsNotNone(spec)
        self.assertIsNotNone(spec.description)
        self.assertEquals(metrics['num_errors'], 0)