[scikit-learn] Release Candidate for Scikit-learn 0.21

Joel Nothman joel.nothman at gmail.com
Tue Apr 30 22:09:55 EDT 2019

PyPI now has source and binary releases for Scikit-learn 0.21rc2.

* Documentation at https://scikit-learn.org/0.21
* Release Notes at https://scikit-learn.org/0.21/whats_new
* Download source or wheels at

Please try out the software and help us edit the release notes before a
final release.

Highlights include:
* neighbors.NeighborhoodComponentsAnalysis for supervised metric learning,
which learns a weighted euclidean distance for k-nearest neighbors.
* ensemble.HistGradientBoostingClassifier
and ensemble.HistGradientBoostingRegressor: experimental implementations of
efficient binned gradient boosting machines.
* impute.IterativeImputer: a non-trivial approach to missing value
* cluster.OPTICS: a new density-based clustering algorithm.
* better printing of estimators as strings, with an option to hide default
parameters for compactness:
* for estimator and library developers: a way to tag your estimator so that
it can be treated appropriately with check_estimator.

There are many other enhancements and fixes listed in the release notes (

Please note that Scikit-learn has new dependencies:
* joblib >= 0.11, which used to be vendored within Scikit-learn
* OpenMP, unless the environment variable SKLEARN_NO_OPENMP=1 when the code
is compiled (and cythonized)

Happy Learning!

>From the Scikit-learn core dev team.
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