Hi, I am running the tests again, but indeed I think the difference in the results comes from that fact that max_features=sqrt(n_features) now by default whereas it was max_features=n_features before.
Gilles On 27 March 2012 11:56, Paolo Losi <[email protected]> wrote: > Thanks Peter, > > On Tue, Mar 27, 2012 at 11:34 AM, Peter Prettenhofer > <[email protected]> wrote: >> >> Paolo, >> >> I noticed that too - maybe @glouppe can comment on this - I think the >> reason was a change in the ``n_features`` heuristic but I might be >> mistaken. > > > Gilles, can you give a quick look to it? If it's not anything obvious just > ping back and I'll try to git bisect the issue... > >> >> Concerning the GaussianNB - there's a PR [1] adressing a critical bug >> in the estimator - it should be merged ASAP. > > > Thank's. I've commented on the PR (the performance regression seems > not to be connected with the PR) > >> >> Furthermore, test time is >> quite low - this might be due to memory layout issues - SGDClassifier >> converts ``coef_`` to fortran-style for increased test-time >> performance. > > > Clear. > > Thanks again > > Paolo > > > ------------------------------------------------------------------------------ > 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
