Hi! Just a general thought.
What do you think about adding data visualization module to scikit-learn? I
mean we often want to look at our data, and having out-of-the-box routines for
high dimension data visualization would be very handy. Unfortunately, I'm not
very familiar with that field, but quite sure there a lot of interesting and
useful methods.
> Date: Fri, 13 Feb 2015 09:34:30 +0100
> From: j...@informatik.uni-bremen.de
> To: scikit-learn-general@lists.sourceforge.net
> Subject: Re: [Scikit-learn-general] GSoC2015 topics
>
> Having Bayesian optimization in sklearn would be great +1
>
> I was working recently on a sklearn-compatible rewrite of Gaussian
> processes. Main features are gradient-based hyperparameter
> optimization, kernel engineering and Gaussian process classification.
> The downside is that it is not completely downward compatible with
> sklearn's current GP interface. I will create a PR in the next days
> where we can discuss the further proceeding (going for merge versus
> adding it to the sklearn-extensions).
>
> Best,
> Jan
>
> On 13.02.2015 00:10, Andy wrote:
> > Sorry, I was using a possibly confusing idiom. The problem with our GP
> > is not so much speed as interface and flexibility.
> > Also, we are not using gradient based parameter optimization.
> >
> > On 02/12/2015 05:48 PM, Artem wrote:
> >> 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
> >> <mailto: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.
> >>
> >>
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> --
> Jan Hendrik Metzen, Dr.rer.nat.
> Team Leader of Team "Sustained Learning"
>
> Universität Bremen und DFKI GmbH, Robotics Innovation Center
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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/
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