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. >> >> >> ------------------------------------------------------------------------------ >> 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 >> <mailto: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 > > > > ------------------------------------------------------------------------------ > 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 -- Jan Hendrik Metzen, Dr.rer.nat. Team Leader of Team "Sustained Learning" Universität Bremen und DFKI GmbH, Robotics Innovation Center FB 3 - Mathematik und Informatik AG Robotik Robert-Hooke-Straße 1 28359 Bremen, Germany Tel.: +49 421 178 45-4123 Zentrale: +49 421 178 45-6611 Fax: +49 421 178 45-4150 E-Mail: j...@informatik.uni-bremen.de Homepage: http://www.informatik.uni-bremen.de/~jhm/ Weitere Informationen: http://www.informatik.uni-bremen.de/robotik ------------------------------------------------------------------------------ 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
