test_standard_scalar.py 文件源码

def test_boston(self):
        from sklearn.datasets import load_boston

        scikit_data = load_boston()
        scikit_model = StandardScaler().fit(scikit_data.data)

        spec = converter.convert(scikit_model, scikit_data.feature_names, 'out').get_spec()

        input_data = [dict(zip(scikit_data.feature_names, row)) 
                for row in scikit_data.data]

        output_data = [{"out" : row} for row in scikit_model.transform(scikit_data.data)]

        metrics = evaluate_transformer(spec, input_data, output_data)

        assert metrics["num_errors"] == 0