Since ensemble methods consistently outperform "traditional" tree building (where variance is controlled by pruning), what are the advantages of implementing pruning in sklearn?
Paolo N.B. The question is not directed specifically to Brain but to GoS applicants and sklearn contributors. On Tue, Mar 13, 2012 at 11:25 AM, Brian Holt <[email protected]> wrote: > Decision trees tend to overfit, so they are most often used (unpruned) in a > forest. That said, I think it would be a useful contribution to our offering. > > Brian ------------------------------------------------------------------------------ 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
