[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`?
If you have 3 score 0.25 0.5 and 0.5, you need to break the tie between the two 0.5. If you use (assuming that lower rank is better)

- maximal rank, you  would have ranks 1, 3, 3
- minimal rank, you would  have ranks 1, 2, 2
- average rank, you would have ranks 1, 2.5, 2.5
- ordinal rank, you would have ranks 1, 2, 3

So depending on how you break your  tie, you might have different performance.