The R2 function in scikit-learn works fine. A negative means that the regression model fits the data worse than a horizontal line representing the sample mean. E.g. you usually get that if you are overfitting the training set a lot and then apply that model to the test set. The econometrics book probably didn't cover applying a model to an independent data or test set, hence the [0, 1] suggestion.
Cheers, Sebastian On Aug 12, 2021, 2:20 PM -0500, Samir K Mahajan <samirkmahajan1...@gmail.com>, wrote: > > Dear Christophe Pallier, Reshama Saikh and Tromek Drabas, > > Thank you for your kind response. Fair enough. I go with you R2 is not a > square. However, if you open any book of econometrics, it says R2 is a > ratio that lies between 0 and 1. This is the constraint. It measures the > proportion or percentage of the total variation in response variable (Y) > explained by the regressors (Xs) in the model . Remaining proportion of > variation in Y, if any, is explained by the residual term(u) Now, > sklearn.matrics. metrics.r2_score gives me a negative value lying on a linear > scale (-5.763335245921777). This negative value breaks the constraint. I just > want to highlight that. I think it needs to be corrected. Rest is up to you . > > I find that Reshama Saikh is hurt by my email. I am really sorry for that. > Please note I never undermine your capabilities and initiatives. You are > great people doing great jobs. I realise that I should have been more > sensible. > > My regards to all of you. > > Samir K Mahajan > > > > > > > > > > On Thu, Aug 12, 2021 at 12:02 PM Christophe Pallier > > <christo...@pallier.org> wrote: > > > Simple: despite its name R2 is not a square. Look up its definition. > > > > > > > On Wed, 11 Aug 2021, 21:17 Samir K Mahajan, > > > > <samirkmahajan1...@gmail.com> wrote: > > > > > Dear All, > > > > > I am amazed to find negative values of sklearn.metrics.r2_score > > > > > and sklearn.metrics.explained_variance_score in a model ( cross > > > > > validation of OLS regression model) > > > > > However, what amuses me more is seeing you justifying negative > > > > > 'sklearn.metrics.r2_score ' in your documentation. This does not > > > > > make sense to me . Please justify to me how squared values are > > > > > negative. > > > > > > > > > > Regards, > > > > > Samir K Mahajan. > > > > > > > > > > _______________________________________________ > > > > > scikit-learn mailing list > > > > > scikit-learn@python.org > > > > > https://mail.python.org/mailman/listinfo/scikit-learn > > > _______________________________________________ > > > scikit-learn mailing list > > > scikit-learn@python.org > > > https://mail.python.org/mailman/listinfo/scikit-learn > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn
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