test_linear_regression.py 文件源码

def test_linear_svr_evaluation(self):
        """
        Check that the evaluation results are the same in scikit learn and coremltools
        """
        ARGS = [ {},
                    {'C': 0.5, 'epsilon': 0.25},
                    {'dual': False, 'loss': 'squared_epsilon_insensitive'},
                    {'tol': 0.005},
                    {'fit_intercept': False},
                    {'intercept_scaling': 1.5}
        ]

        input_names = self.scikit_data.feature_names
        df = pd.DataFrame(self.scikit_data.data, columns=input_names)

        for cur_args in ARGS:
            print(cur_args)
            cur_model = LinearSVR(**cur_args)
            cur_model.fit(self.scikit_data['data'], self.scikit_data['target'])
            spec = convert(cur_model, input_names, 'target')

            df['prediction'] = cur_model.predict(self.scikit_data.data)

            metrics = evaluate_regressor(spec, df)
            self.assertAlmostEquals(metrics['max_error'], 0)