Do you have any particular ideas on how one could speedup GPs, besides
reimplementing it in Cython? Looks like spearmint is completely pythonic,
so they either as slow (or slower), or use different algorithm (I'm not
very familiar with approaches to GPs).
On Fri, Feb 13, 2015 at 12:41 AM, Andy <t3k...@gmail.com> wrote:
>
> On 02/12/2015 04:47 AM, Artem wrote:
>
> There are several packages (spearmint, hyperopt, MOE) offering Bayesian
> Optimization to the problem of choosing hyperparameters. Wouldn't it be
> nice to add such *Search[CV] to sklearn?
>
> Yes. I haven't really looked much into the spearmint approach, but before
> we could do anything with GPs I am afraid we need to get our GP up to speed.
>
>
> ------------------------------------------------------------------------------
> Dive into the World of Parallel Programming. The Go Parallel Website,
> sponsored by Intel and developed in partnership with Slashdot Media, is
> your
> hub for all things parallel software development, from weekly thought
> leadership blogs to news, videos, case studies, tutorials and more. Take a
> look and join the conversation now. http://goparallel.sourceforge.net/
> _______________________________________________
> Scikit-learn-general mailing list
> Scikit-learn-general@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>
>
------------------------------------------------------------------------------
Dive into the World of Parallel Programming. The Go Parallel Website,
sponsored by Intel and developed in partnership with Slashdot Media, is your
hub for all things parallel software development, from weekly thought
leadership blogs to news, videos, case studies, tutorials and more. Take a
look and join the conversation now. http://goparallel.sourceforge.net/
_______________________________________________
Scikit-learn-general mailing list
Scikit-learn-general@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
