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
