python - multilabel classification with OneVsOneClassifier -


is possible 1 multilabel classification onevsoneclassifier?

i made classification of onevsrestclassifier follows:

lb = preprocessing.multilabelbinarizer()  y = lb.fit_transform(y_train)  classifier = pipeline([     ('vectorizer',countvectorizer()),     ('tfidf',tfidftransformer()),     ('clf',onevsrestclassifier(svc(kernel='linear')))])   classifier.fit(x_train,y) predicted = classifier.predict(x_test) all_label = lb.inverse_transform(predicted) print all_label

but use onevsoneclassifier returns error indicating excessive number of labels.


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