92bba3102bed7256aa22c0ab273139048aa23559,yellowbrick/classifier.py,ClassifierReport,score,#ClassifierReport#Any#Any#,78

Before Change

            "labels": kwargs.pop("labels", None),
            "target_names": kwargs.pop("target_names", None),
            "sample_weight": kwargs.pop("sample_weight", None),
            "digits": kwargs.pop("digits", 2)
        }

        self.report = classification_report(y_true, y_pred, **cr_kwargs)

After Change

        
        Generates the Scikit-Learn classification_report
        
        self.keys = ("precision", "recall", "f1")
        self.scores = precision_recall_fscore_support(y, y_pred, labels=self.classes)
        self.scores = map(lambda s: dict(zip(self.classes, s)), self.scores[0:3])
        self.scores = dict(zip(self.keys, self.scores))
        self._draw(y, y_pred)


    def _draw(self, y, y_pred):

Instances