2011/12/3 Gael Varoquaux <[email protected]>: > On Sat, Nov 19, 2011 at 09:15:43PM -0500, James Bergstra wrote: > > thinking about this for quite a while. I am thrilled to know that it > actually works, and would be _very_ interested about having this in the > scikit. Let's discuss it at the sprints.
Alexandre has a new blog post about this with simple python snippet using sklearn GuassianProcess: http://atpassos.posterous.com/bayesian-optimization > With regards to the random sampling, I am a bit worried that the results > hold for a fair amount of points, and with a small amount of points > (which is typically the situation in which many of us hide) it becomes > very sensitive to the seed. I guess you should monitor the improvement before deciding to stop the search. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ 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 [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
