I'm primarily thinking svm for which it looks horrible. Actually out of
svm, trees and logistic regression - log reg is the best. Just to confirm,
gridsearch uses score which returns R^2 yes? Getting negative scores with
svm and gridsearch was confusing
On Jan 24, 2013 11:51 AM, "Flavio Vinicius" <flavio...@gmail.com> wrote:
> I think you can only guarantee that R2 is always positive when
> performing linear regression with no constraints. Is this you case, or
> are you using another model? For example, when using a regression
> forest you cannot guarantee positive R2.
>
> Better explanation here:
>
> http://stats.stackexchange.com/questions/12900/when-is-r-squared-negative
> --
> Flavio
>
>
> On Thu, Jan 24, 2013 at 11:28 AM, Bertrand Thirion
> <bertrand.thir...@inria.fr> wrote:
> > If you use a cross validation scheme, where you estimate the residuals
> > variance on left-out data and compare it to the variance of the model
> with
> > the intercept only, then R^2 can be negative. This approach is an
> > alternative to adjusted R^2 for model selection, and probably makes more
> > sense when the model is penalized (i.e. you're no longer doing maximum
> > likelihood).
> > May be there's a more proper statistical term for that ?
> > HTH
> >
> > Bertrand
> >
> > ________________________________
> >
> > De: "Ronnie Ghose" <ronnie.gh...@gmail.com>
> > À: scikit-learn-general@lists.sourceforge.net
> > Envoyé: Jeudi 24 Janvier 2013 12:57:27
> > Objet: Re: [Scikit-learn-general] (no subject)
> >
> >
> > is it adjusted R^2? The usual R^2 can never be negative afaik
> >
> > http://en.wikipedia.org/wiki/Coefficient_of_determination
> >
> >
> > On Wed, Jan 23, 2013 at 2:42 PM, Andreas Mueller <
> amuel...@ais.uni-bonn.de>
> > wrote:
> >>
> >> Am 23.01.2013 20:32, schrieb Ronnie Ghose:
> >> > How can _best_score in GridSearchCV be negative? R^2 can only be from
> >> > 0 to -1 ...?
> >> R^2 can also be negative afaik. It is somewhat unstable for small sample
> >> sizes.
> >>
> >>
> >>
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