model.py 文件源码

def _get_scorings(self):
        """Get scorings for this problem type.

        Returns
        -------
        scorings : list of dict
            Information on metric name and associated "scoring" as defined in
            sklearn.metrics
        scorings_ : list
            List of "scoring" as defined in sklearn.metrics. This is a "utility
            variable" that can be used where we just need the names of the
            scoring functions and not the more complete information.
        """
        # scoring_types maps user-readable name to `scoring`, as argument to
        # cross_val_score
        # See also http://scikit-learn.org/stable/modules/model_evaluation.html#scoring-parameter
        if self._is_classification():
            scorings = Model.CLASSIFICATION_SCORING
            scorings_= [s["scoring"] for s in scorings]
        elif self._is_regression():
            scorings = Model.REGRESSION_SCORING
            scorings_= [s["scoring"] for s in scorings]
        else:
            raise NotImplementedError

        return scorings, scorings_