On Sat, Dec 03, 2011 at 12:32:59PM +0100, Olivier Grisel wrote: > Alexandre has a new blog post about this with simple python snippet > using sklearn GuassianProcess:
> http://atpassos.posterous.com/bayesian-optimization That's pretty cool. If Alexandre agrees, this code could definitely serve as the basis for a scikit-learn implementation: it is simple and readable, looks very testable, and brings in the necessary functionality. G ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-novd2d _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
