A quick follow-up on my previous email: >> On 25 March 2012 03:49, Olivier Grisel <[email protected]> wrote: >>> [..] >>> >>> Another way to rephrase that question: what is the typical sweet spot >>> for the dataset shape when doing classification Gradient Boosted >>> Trees? What are reasonable values for the number of estimators in >>> various application domains?
GBRT is relatively robust w.r.t. overfitting if you use shrinkage ( see the docs). The choice of the number of estimators is mainly governed by the available computational resources. As usual you have to balance between training vs. test time performance - if you don't care about test time performance you should use as much base learners as you can afford**. If test time performance matters (e.g. latency constraints in a web app) things look different :-) ** I remember that a student of mine once used more than 10K base learners for the yahoo learning to rank competition. >>> >>> -- >>> Olivier >>> http://twitter.com/ogrisel - http://github.com/ogrisel >>> >>> ------------------------------------------------------------------------------ >>> This SF email is sponsosred by: >>> Try Windows Azure free for 90 days Click Here >>> http://p.sf.net/sfu/sfd2d-msazure >>> _______________________________________________ >>> Scikit-learn-general mailing list >>> [email protected] >>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> >> ------------------------------------------------------------------------------ >> This SF email is sponsosred by: >> Try Windows Azure free for 90 days Click Here >> http://p.sf.net/sfu/sfd2d-msazure >> _______________________________________________ >> Scikit-learn-general mailing list >> [email protected] >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > -- > Peter Prettenhofer -- Peter Prettenhofer ------------------------------------------------------------------------------ This SF email is sponsosred by: Try Windows Azure free for 90 days Click Here http://p.sf.net/sfu/sfd2d-msazure _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
