Awesome! Thanks to the contributors On Tue, Jul 19, 2016 at 9:44 PM, Nelson Liu <[email protected]> wrote:
> Congrats! These look great, thanks to both the authors and the > scikit-learn-contrib organizers for putting this together. > > Nelson > > On Tue, Jul 19, 2016 at 9:09 AM Mathieu Blondel <[email protected]> > wrote: > >> Hi everyone, >> >> We are pleased to announce that three new projects recently joined >> scikit-learn-contrib! >> >> * imbalanced-learn: >> https://github.com/scikit-learn-contrib/imbalanced-learn >> >> Python module to perform under sampling and over sampling with various >> techniques. >> >> * polylearn: https://github.com/scikit-learn-contrib/polylearn >> >> Factorization machines and polynomial networks for classification and >> regression in Python. >> >> * forest-confidence-interval: >> https://github.com/scikit-learn-contrib/forest-confidence-interval >> >> Confidence intervals for scikit-learn forest algorithms. >> >> We thank the respective authors for their neat contribution to the >> scikit-learn ecosystem! >> >> Cheers, >> Mathieu >> _______________________________________________ >> scikit-learn mailing list >> [email protected] >> https://mail.python.org/mailman/listinfo/scikit-learn >> > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn > >
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