Hi all. I know quite a few GP people, and most agree that the GPs in sklearn are not super useful. GPs are a pretty wide field, and we will probably not implement all the fancy stuff that is out there, but I feel that if we have a GP implementation, it should hold up to the sklearn standards and be reasonably useful for non-expert users.
I just talked with Dan, the author the GP library george http://dan.iel.fm/george/current/ . He said that one of the reasons the current GP is not so great is that it is unclear how to specify advanced kernels. Most standard examples, like this one http://dan.iel.fm/george/current/user/hyper/ use kernels that are a combination of the basic primitive kernels. My question is basically: do you think it would be worth adding a way to easily specify and combine kernels, similar to the way that is done in GPy? Or should we leave that to GPy? Then the question is how useful our implementation is without it :-/ Cheers, Andy ------------------------------------------------------------------------------ Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server from Actuate! Instantly Supercharge Your Business Reports and Dashboards with Interactivity, Sharing, Native Excel Exports, App Integration & more Get technology previously reserved for billion-dollar corporations, FREE http://pubads.g.doubleclick.net/gampad/clk?id=157005751&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
