(self, X, y, **score_params)
return result
Performance evaluation with a default metric.

        Parameters
        ----------
        X :
            Features.
        y:
            Ground truth labels.
        score_params:
            Any additional parameters expected by the score function of
            the underlying operator.
        Returns
        -------
        score :
            performance metric value
Performance evaluation with a default metric.
Performance evaluation with a default metric .
def score(self, X, y, **score_params) -> Any:
        """Performance evaluation with a default metric.

        Parameters
        ----------
        X :
            Features.
        y:
            Ground truth labels.
        score_params:
            Any additional parameters expected by the score function of
            the underlying operator.
        Returns
        -------
        score :
            performance metric value
        """
        # Use the input schema of predict as in most cases it applies to score as well.
        X = self._validate_input_schema("X", X, "predict")
        if score_params is None:
            result = self._impl_instance().score(X, y)
        else:
            result = self._impl_instance().score(X, y, **score_params)
        # We skip output validation for score for now
        return result
def score ( self , X , y , * * score_params ) -> Any : # Use the input schema of predict as in most cases it applies to score as well. X = self . _validate_input_schema ( "X" , X , "predict" ) if score_params is None : result = self . _impl_instance ( ) . score ( X , y ) else : result = self . _impl_instance ( ) . score ( X , y , * * score_params ) # We skip output validation for score for now return result