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

[Gael Varoquaux]

Thank you all and congratulations indeed.

Because this release comes soon after the latest one from the 0.20
series, we might have thought that it would be a light one. But no!
Plenty of exciting features!

Gaël

On Wed, May 01, 2019 at 10:13:02PM -0400, Andreas Mueller wrote:
> Thank you for all the amazing work y'all!


> On 4/30/19 10:09 PM, Joel Nothman wrote:

>     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 https://pypi.org/project/scikit-learn/
>     0.21rc2/

>     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. https:/
>     /scikit-learn.org/0.21/modules/neighbors.html#nca
>     * ensemble.HistGradientBoostingClassifier
>     and ensemble.HistGradientBoostingRegressor: experimental implementations of
>     efficient binned gradient boosting machines. https://scikit-learn.org/0.21/
>     modules/ensemble.html#gradient-tree-boosting
>     * impute.IterativeImputer: a non-trivial approach to missing value
>     imputation. https://scikit-learn.org/0.21/modules/impute.html#
>     multivariate-feature-imputation
>     * cluster.OPTICS: a new density-based clustering algorithm. https://
>     scikit-learn.org/0.21/modules/clustering.html#optics
>     * better printing of estimators as strings, with an option to hide default
>     parameters for compactness: https://scikit-learn.org/0.21/auto_examples/
>     plot_changed_only_pprint_parameter.html
>     * for estimator and library developers: a way to tag your estimator so that
>     it can be treated appropriately with check_estimator. https://
>     scikit-learn.org/0.21/developers/contributing.html#estimator-tags

>     There are many other enhancements and fixes listed in the release notes (
>     https://scikit-learn.org/0.21/whats_new).

>     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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-- 
    Gael Varoquaux
    Senior Researcher, INRIA 
    http://gael-varoquaux.info            http://twitter.com/GaelVaroquaux