def test_multilabel():
 (X, y) = make_multilabel_classification(n_classes=2, n_labels=1, allow_unlabeled=False, random_state=123)
 clf = OneVsRestClassifier(SVC(kernel='linear'))
 eclf = VotingClassifier(estimators=[('ovr', clf)], voting='hard')
 try:
  eclf.fit(X, y)
 except NotImplementedError:
  return

def test_multilabel ( ) : ( X , y ) = make_multilabel_classification ( n_classes = 2 , n_labels = 1 , allow_unlabeled = False , random_state = 123 ) clf = OneVsRestClassifier ( SVC ( kernel = 'linear' ) ) eclf = VotingClassifier ( estimators = [ ( 'ovr' , clf ) ] , voting = 'hard' ) try : eclf . fit ( X , y ) except NotImplementedError : return
check if error is raised for multilabel classification .