2012/1/20 Andreas <[email protected]>: > In how far is #491 tree specific? > This is parallelization over different boot strap samples. > Or am I missing something there? > Feature importance (#478) is not as generic but > "just" relies on feature importance from the base classifier, > right? > Or did I miss something there, too?
I didn't follow that PR and was surprised that it depended on decision trees when I saw it after the merge. Prinzie and Van den Poel [1][2] build random "forests" of multinomial LR classifiers, calling the result random multinomial logit. I've yet to read it thorougly, so I'm not sure they use the exact same (meta-)algorithm that our forests do. [1] http://www.sciencedirect.com/science/article/pii/S0957417407000498 [2] https://en.wikipedia.org/wiki/Random_multinomial_logit -- Lars Buitinck Scientific programmer, ILPS University of Amsterdam ------------------------------------------------------------------------------ Keep Your Developer Skills Current with LearnDevNow! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-d2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
