test_composite_pipelines.py 文件源码

def test_boston_OHE_plus_normalizer(self): 

        data = load_boston()

        pl = Pipeline([
            ("OHE", OneHotEncoder(categorical_features = [8], sparse=False)), 
            ("Scaler",StandardScaler())])

        pl.fit(data.data, data.target)

        # Convert the model
        spec = convert(pl, data.feature_names, 'out')

        input_data = [dict(zip(data.feature_names, row)) for row in data.data]
        output_data = [{"out" : row} for row in pl.transform(data.data)]

        result = evaluate_transformer(spec, input_data, output_data)

        assert result["num_errors"] == 0