(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
while we're at it:

aN inner loop

closed form


On Sunday, October 19, 2014, Alexandre Gramfort <notifications@github.com>
wrote:

> In nilearn/decoding/fista.py:
>
> > @@ -0,0 +1,241 @@
> > +"""
> > +Generic FISTA for solving TV-l1, S-Lasso, etc., problems.
> > +For problems on which the prox of the nonsmooth term cannot be computed
> > +closed-form (e.g TV-l1), approximate it using a inner FISTA loop.
>
> in closed-form
>
> in is missing
>
> —
> Reply to this email directly or view it on GitHub
> <https://github.com/nilearn/nilearn/pull/219/files#r19061211>.
>