[scikit-learn] imbalanced-learn 0.3.0 is chasing scikit-learn 0.19.0

[Guillaume Lemaître]

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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