I think just moving from a train set to a test set would be problematic for small n_samples.
Vlad On Apr 17, 2012, at 15:48 , Olivier Grisel wrote: > Le 17 avril 2012 05:39, Gael Varoquaux <[email protected]> a > écrit : >> On Tue, Apr 17, 2012 at 03:35:26PM +0300, Dimitrios Pritsos wrote: >>> If you would like the opinion of user (i.e. me) I think this is the best >>> solution for intuitive use of the Lib. And having scale_C=False as >>> default. >> >> For small number of samples, _it does not work_. Period, there is not >> libsvm or not libsvm convention debate. > > _it does not work_ => grid search / model selection does not work. I > am pretty sure the vast majority of our users do not do systematic > grid search for C either unfortunately :( > > -- > Olivier > http://twitter.com/ogrisel - http://github.com/ogrisel > > ------------------------------------------------------------------------------ > Better than sec? Nothing is better than sec when it comes to > monitoring Big Data applications. Try Boundary one-second > resolution app monitoring today. Free. > http://p.sf.net/sfu/Boundary-dev2dev > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ Better than sec? Nothing is better than sec when it comes to monitoring Big Data applications. Try Boundary one-second resolution app monitoring today. Free. http://p.sf.net/sfu/Boundary-dev2dev _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
