Extra Trees are even more random than random forests. Have a look at the referenced papers.
To choose one vs the other you can evaluate the generalization power via cross-validation on your data (you might also want to grid search the optimal parameter values for max_features and min_samples_split and maybe other parameters). In general, extra trees tend to be larger (deeper trees) than random forests. For equal sized models they tend to be faster to train. -- Olivier ------------------------------------------------------------------------------ Android™ apps run on BlackBerry®10 Introducing the new BlackBerry 10.2.1 Runtime for Android apps. Now with support for Jelly Bean, Bluetooth, Mapview and more. Get your Android app in front of a whole new audience. Start now. http://pubads.g.doubleclick.net/gampad/clk?id=124407151&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
