2013/12/22 Juan Nunez-Iglesias <jni.s...@gmail.com>: > On Sat, Dec 21, 2013 at 10:28 AM, Peter Prettenhofer > <peter.prettenho...@gmail.com> wrote: >> >> Actually, I'd propose to turn off multiprocessing at prediction time - >> this might backfire quite easily. > > > For the more ignorant among us, can you give an example? I don't understand > why this would be true, especially in the case of random forests...?
As we now have a low latency, no-memory copy RandomForest.fit method, the users might not expect memory duplication or higher latency at prediction time when n_jobs != 1. But thanks to Gilles releasing the GIL in the predict method of the trees we now also use the threading backend in the predict function. So we can keep parallelization enabled at prediction time as well. Any other review to merge this PR? -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ Rapidly troubleshoot problems before they affect your business. Most IT organizations don't have a clear picture of how application performance affects their revenue. With AppDynamics, you get 100% visibility into your Java,.NET, & PHP application. Start your 15-day FREE TRIAL of AppDynamics Pro! http://pubads.g.doubleclick.net/gampad/clk?id=84349831&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
