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: http://contrib.scikit-learn.org/imbalanced-learn/stable/whats_new.html#version-0-3 A big thank you to contributors to use, raise issues, and submit PRs to imblearn. -- Guillaume Lemaitre
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