labels.py 文件源码

def _fit(self, X, Y_labels, **kwargs):
        Y_labels_filtered = filter_labels(Y_labels, include=self.include, exclude=self.exclude)
        self.label_binarizer_ = MultiLabelBinarizer(sparse_output=False).fit(Y_labels_filtered)
        logger.info('{} labels found in training instances.'.format(len(self.classes_)))

        if not len(self.classes_): raise ValueError('There are no labels available for fitting model.')

        return super(MultiLabelsClassifier, self)._fit(X, Y_labels_filtered, **kwargs)
    #end def