I would also add that probably ensemble are slower to train then prunned tree. In academic, this is not a too big problem, but in industries it can be important in some case.
Fred On Tue, Mar 13, 2012 at 7:34 AM, Paolo Losi <[email protected]> wrote: > On Tue, Mar 13, 2012 at 12:09 PM, Andreas <[email protected]> wrote: >> On 03/13/2012 12:11 PM, Paolo Losi wrote: >>> Since ensemble methods consistently outperform "traditional" tree building >>> (where variance is controlled by pruning), what are the advantages of >>> implementing >>> pruning in sklearn? >>> >>> >> I think the idea would be to have an easy to interpret model. >> There might be applications where this is beneficial. >> >> Also, I think having well-known models in sklearn is a good >> idea, even if they are not top-performing. > > That's fair enough. Thanks > > Paolo > > ------------------------------------------------------------------------------ > 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 ------------------------------------------------------------------------------ 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
