[WIP] Strong rules for coordinate descent

Fixes https://github.com/scikit-learn/scikit-learn/issues/229

This implements strong rules for discarding non active features in coordinate descent. I believe this works. However it is really slow. 

TODO:

- [ ] Decide whether to migrate the strong_active_set and check_kkt_conditions to Cython
- [ ] Fix the lazy centering of sparse matrices that gives slightly different results.
In the sparse case it might be faster using
```python
feature = np.zeros(X.shape[0])
start, stop = X.indptr[i:i+2]
feature[X.indices[start:stop]] = X.data[start:stop]
```