2011/12/5 Alexandre Passos <[email protected]>: > On Mon, Dec 5, 2011 at 16:26, James Bergstra <[email protected]> wrote: >> >> This is definitely a good idea. I think randomly sampling is still >> useful though. It is not hard to get into settings where the grid is >> in theory very large and the user has a budget that is a tiny fraction >> of the full grid. > > I'd like to implement this, but I'm stuck on a nice way of specifying > distributions over each axis (i.e., sometimes you want to sample > across orders of magnitude (say, 0.001, 0.01, 0.1, 1, etc), sometimes > you want to sample uniformly (0.1, 0.2, 0.3, 0.4 ...)) that is obvious > and readable and flexible.
You should discuss this with Gael next week during NIPS. I tend to use np.logspace and np.linspace to build my grids. -- 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
