utils_scoring.py 文件源码

def score(self, estimator, X, y, took_log_of_y=False, advanced_scoring=False, verbose=2, name=None):
        X, y = utils.drop_missing_y_vals(X, y, output_column=None)

        if isinstance(estimator, GradientBoostingRegressor):
            X = X.toarray()

        predictions = estimator.predict(X)

        if took_log_of_y:
            for idx, val in enumerate(predictions):
                predictions[idx] = math.exp(val)

        try:
            score = self.scoring_func(y, predictions)
        except ValueError:

            bad_val_indices = []
            for idx, val in enumerate(y):
                if str(val) in bad_vals_as_strings:
                    bad_val_indices.append(idx)

            predictions = [val for idx, val in enumerate(predictions) if idx not in bad_val_indices]
            y = [val for idx, val in enumerate(y) if idx not in bad_val_indices]

            print('Found ' + str(len(bad_val_indices)) + ' null or infinity values in the y values. We will ignore these, and report the score on the rest of the dataset')
            score = self.scoring_func(y, predictions)

        if advanced_scoring == True:
            if hasattr(estimator, 'name'):
                print(estimator.name)
            advanced_scoring_regressors(predictions, y, verbose=verbose, name=name)
        return - 1 * score