| Merci beaucoup. Super utile. J' ai d'ailleurs introduit ton module a la conference data intelligence a Capital One il y a moins de 2 mois ( en banlieue de Washington DC). Sent from my BlackBerry 10 Darkphone
We are excited to announce the new release of the scikit-learn-contrib imbalanced-learn, already available through conda and pip (cf. the installation page https://tinyurl.com/y92flbab for more info)
Notable add-ons are: * Support of sparse matrices * Support of multi-class resampling for all methods * A new BalancedBaggingClassifier using random under-sampling chained with the scikit-learn BaggingClassifier * Creation of a didactic user guide * New API of the ratio parameter to fit the needs of multi-class resampling * Migration from nosetests to pytest You can check the full changelog at: A big thank you to contributors to use, raise issues, and submit PRs to imblearn. -- Guillaume Lemaitre | ||
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