On Tue, Feb 04, 2014 at 10:32:12AM +0200, Nick Pentreath wrote:
> Are some of the algorithms too cutting edge or not cited enough,

Yes

> or some other reason?

I think that it is good practice to explore new ideas outside of
scikit-learn. It usually takes a lot of effort and time to figure out
whether an approach will be a lot of benefits or not.

Gaƫl


> On Tue, Feb 4, 2014 at 10:28 AM, Gael Varoquaux 
> <gael.varoqu...@normalesup.org>
> wrote:

>     On Tue, Feb 04, 2014 at 09:04:00AM +0100, Alexandre Gramfort wrote:
>     > > Alex had provided me a link to this gist,
>     > > https://gist.github.com/fabianp/3097107 . Sorry for sounding dumb, but
>     is
>     > > this one of the "strong rules"?

>     > yes

>     http://arxiv.org/pdf/1011.2234

>     > > And one last question, what about generalized additive models? Would
>     that be
>     > > a good GSoC project to do?

>     > I am +0 on this now. I suggested MARS/EARTH as there is already some 
> code
>     > which would facilitate success.

>     I would personnally be more excited about merging in the fast logistic
>     regression and SVM from lightning https://github.com/mblondel/lightning.

>     G

>     
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-- 
    Gael Varoquaux
    Researcher, INRIA Parietal
    Laboratoire de Neuro-Imagerie Assistee par Ordinateur
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