demo script for scikit-multilearn. should be executed in /path/to/scikit-multilearn.

skmulti_demo.py

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)