ENH + TST generalized and test unique_labels
ENH extend zero_one_loss to multilabel output
ENH add hamming_loss metrics
TST add representation and shuffling invariance
COSMIT + TST more test for Hamming loss
ENH add multi-label support for accuracy_score
TST hamming loss labels inference
COSMIT pep8
DOC now there is multilabels metrics
Update what's new
DOC improve parameter description
FIX missing import in doctest
TST more tests for unique_labels
DOC rename label binary matrix to label indicator matrix
What's new : add credit
COSMIT less decorative comment
ENH unique_classes is now a function of the multiclass module
DOC add example and a small narrative doc
ENH (corner case) + DOC + TST for is_multilabel and is_label_indicator_matrix
ENH create a sklearn.utils.multiclass module