[MRG] ENH add coverage multilabel ranking metric

This pr adds the coverage multilabel ranking metric in scikit-learn.

It's very useful as it carries a lot of intuition on your estimator performance. This is the average number of ~~true~~ labels that you need to predict in order to avoid missing any true one given your y_score matrix.

@jnothman Do you see an easy way to make this works with sparse csc `y_true`?
how about support for just labels? In that way you can do a LabelBinarizer().fit_transform(y_true) to get the binary indicator format and raise an error, if len(labels) != y_score.shape[1]