cd1a5446ce793d09f28d021c466a279301eb51f0,deslib/des/meta_des.py,METADES,select,#METADES#,294

Before Change

        // if no classifier was selected, use the whole pool
        if len(indices) == 0:
            indices = list(range(self.n_classifiers))

        return indices

    def estimate_competence(self, query, predictions=None):

After Change

                               Boolean matrix containing True if the base classifier is select, False otherwise

        
        if competences.ndim < 2:
            competences = competences.reshape(1, -1)

        selected_classifiers = (competences > self.selection_threshold)
        // For the rows that are all False (i.e., no base classifier was selected, select all classifiers (all True)
        selected_classifiers[~np.any(selected_classifiers, axis=1), :] = True

Instances