if self.selection_threshold is None:
self.selection_threshold = 1.0/self.n_classes
indices = [clf_index for clf_index, clf_competence in enumerate(competences)
if clf_competence > self.selection_threshold]
if len(indices) == 0:
indices = list(range(self.n_classifiers))
return indices
@staticmethod
def potential_func(dist):
After Change
indices = (competences > self.selection_threshold)
// For the rows that are all False (i.e., no base classifier was selected, select all classifiers (all True)
indices[~np.any(indices, axis=1), :] = True
return indices
