test_random_forest_regression_numeric.py 文件源码

def _train_convert_evaluate(self, **scikit_params):
        """
        Train a scikit-learn model, convert it and then evaluate it with CoreML
        """
        scikit_model = RandomForestRegressor(random_state = 1, **scikit_params)
        scikit_model.fit(self.X, self.target)

        # Convert the model
        spec = skl_converter.convert(scikit_model, self.feature_names, self.output_name)

        # Get predictions
        df = pd.DataFrame(self.X, columns=self.feature_names)
        df['prediction'] = scikit_model.predict(self.X)

        # Evaluate it
        metrics = evaluate_regressor(spec, df, verbose = False)
        return metrics