[MRG] Sparse One vs. Rest

This is a PR for the other parts in PR #2458 concerning sparse output support for the ovr classier. This branch was made off of the sprs-lbl-bin branch from PR #3203 and will be rebased to remove all the sparse label binarizer additions from the diff once the pull request is merged.

Benchmark Experiments using PR #2828 for data generation:
- [x] ```fit_ovr```: ```sparse_output=True``` VS. ```sparse_output=sp.issparse(y)```
- [x] ```fit_ovr``` With input as CSR matrix: Cast to CSC before column extraction VS. Leave as CSR
- [x] Memory profiling for sparse vs. dense target data
- [x] Test the changes to label.py
- [x] Test probability and desicion functions after fitting on sparse target data
- [ ] Memory benchmark with ```njobs != 1```
That's an interesting idea... Presumably the reissue would need to be outside of the context manager, and using [`warn_explicit`](https://docs.python.org/2/library/warnings.html). It would be nice to test that nested calls to `assert_warns` worked. At the same time, I see this creating problems where the same warning had been issued multiple times inside the tested method.

I don't really think this needs to be a concern of this PR. Warnings are messy.