Actually, it turns out I was incorrect. According to the docs: http://scikit-learn.org/stable/modules/ensemble.html#forests-of-randomized-trees
"each tree in the ensemble is built from a sample drawn with replacement (i.e., a bootstrap sample) from the training set. In addition, when splitting a node during the construction of the tree, the split that is chosen is no longer the best split among all features. Instead, the split that is picked is the best split among a random subset of the features." On Sat, Oct 27, 2012 at 7:51 AM, Richard T. Guy <[email protected]> wrote: > That explains the confusion! > > Thanks, guys. > > Tommy > > On Sat, Oct 27, 2012 at 5:25 AM, Joseph Turian <[email protected]> > wrote: >> Gilles, >> >> I met Tommy Guy at the pydata conference today. >> If I remember correctly, Brian Eoff (I don't have his email address) >> errantly said that random forests partitions/samples the features >> before creating each tree. I didn't want to correct him in front of >> the audience, and it slipped my mind to mention it to him later. >> >> But I remembered when Tommy Guy asked the question. >> >> Joseph >> >> On Sat, Oct 27, 2012 at 5:16 AM, Gilles Louppe <[email protected]> wrote: >>> Hi, >>> >>>> I know the speaker at pydata today claimed that the features are >>>> partitioned, >>> >>> Can you elaborate? If you pick your features prior to the construction >>> of the tree and then build it on that subset only, then indeed, this >>> is not random forest. That algorithm is called Random Subspaces. >>> >>> Best, >>> >>> Gilles >>> >>> ------------------------------------------------------------------------------ >>> WINDOWS 8 is here. >>> Millions of people. Your app in 30 days. >>> Visit The Windows 8 Center at Sourceforge for all your go to resources. >>> http://windows8center.sourceforge.net/ >>> join-generation-app-and-make-money-coding-fast/ >>> _______________________________________________ >>> Scikit-learn-general mailing list >>> [email protected] >>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> >> >> >> -- >> Joseph Turian, Ph.D. | President, MetaOptimize >> "Optimize Profits. Optimize Engagement." >> http://metaoptimize.com >> 855-ALL-DATA >> >> The web's most active forum for data scientists: http://metaoptimize.com/qa/ >> >> ------------------------------------------------------------------------------ >> WINDOWS 8 is here. >> Millions of people. Your app in 30 days. >> Visit The Windows 8 Center at Sourceforge for all your go to resources. >> http://windows8center.sourceforge.net/ >> join-generation-app-and-make-money-coding-fast/ >> _______________________________________________ >> Scikit-learn-general mailing list >> [email protected] >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > ------------------------------------------------------------------------------ > WINDOWS 8 is here. > Millions of people. Your app in 30 days. > Visit The Windows 8 Center at Sourceforge for all your go to resources. > http://windows8center.sourceforge.net/ > join-generation-app-and-make-money-coding-fast/ > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- Joseph Turian, Ph.D. | President, MetaOptimize "Optimize Profits. Optimize Engagement." http://metaoptimize.com 855-ALL-DATA The web's most active forum for data scientists: http://metaoptimize.com/qa/ ------------------------------------------------------------------------------ WINDOWS 8 is here. Millions of people. Your app in 30 days. Visit The Windows 8 Center at Sourceforge for all your go to resources. http://windows8center.sourceforge.net/ join-generation-app-and-make-money-coding-fast/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
