[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`?
Sample_weights is here. But you don't support them at least from the function signature. But I think it is as trivial as adding `np.average` instead of `np.mean`