(WIP) Sparse models: S-LASSO and TV-l1

- Supports TV-l1 and S-LASSO priors
- Supports logistic and squared losses
- Has cross validation
- Can automatically select alpha by CV (+ automatic computation of useful alpha ranges for the CV)
- Warning: User must supply l1_ratio
I think that we need two subclasses: one SpaceNetClassifier and one SpaceNetRegressor. These would simply set this parameter (which you could move to a class parameter, that way you don't have to override the init).

The benefit is that it makes it more explicit for the user, and thus reduces the risk of human error.

What do you think, @agramfort ?