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- from skmultilearn.dataset import Dataset
- from skmultilearn.meta.br import BinaryRelevance
- from sklearn.svm import SVC
- from sklearn.metrics import hamming_loss
- train_set=Dataset.load_dataset_dump("skmultilearn/data/scene-train.dump.bz2")
- test_set=Dataset.load_dataset_dump("skmultilearn/data/scene-test.dump.bz2")
- clf=BinaryRelevance(SVC(kernel="linear"))
- clf.fit(train_set["X"],train_set["y"])
- ypred=clf.predict(test_set["X"])
- # evaluate the performance using hamming loss. lower is better.
- print hamming_loss(test_set["y"],ypred)
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