Congrats, everyone! To me the most exciting part is HistGradientBoostingRegressor and HistGradientBoostingClassifier no longer being experimental, especially with their native handling of categorical variables (no more unnecessary compromises of choosing a particular numeric encoding strategy!) and of missing values** (without imputation).
This finally puts scikit-learn in the same class as R implementations for tree-based gradient boosting. **(Since it treats feature missingness as a predictive value we just have to be careful that the missingness does not have target leakage by being target-correlated in any way that won't be in effect at prediction time in production, e.g. if the feature was often simply not stored whenever the target turned out negative.) - David Rosen On Mon, Sep 27, 2021 at 4:06 AM Gael Varoquaux < gael.varoqu...@normalesup.org> wrote: > Thank you to Adrin for stewarding this release, and congratulation to all > the team for merging all the improvements. > > Scikit-learn is a foundation of machine learning in Python. Solid > releases and stability over time is a service to the community. > > Gaël > > On Fri, Sep 24, 2021 at 06:38:40PM +0200, Adrin wrote: > > Hi everyone, > > > We're happy to announce the 1.0 release which you can install via pip or > conda: > > > pip install -U scikit-learn > > > or > > > conda install -c conda-forge scikit-learn > > > You can read the release highlights under > https://scikit-learn.org/stable/ > > auto_examples/release_highlights/plot_release_highlights_1_0_0.html and > the > > long list of the changes under > https://scikit-learn.org/stable/whats_new/ > > v1.0.html > > > New major features include: mandatory keyword arguments in many places, > Spline > > Transformers, Quantile Regressor, Feature Names Support, a more flexible > > plotting API, Online One-Class SVM, and much more! > > > This version supports Python versions 3.7 to 3.9. > > > A big thanks to all contributors for making this release possible. > > > Regards, > > Adrin, > > On the behalf of the scikit-learn maintainer team. > > > _______________________________________________ > > scikit-learn mailing list > > scikit-learn@python.org > > https://mail.python.org/mailman/listinfo/scikit-learn > > > -- > Gael Varoquaux > Research Director, INRIA > http://gael-varoquaux.info http://twitter.com/GaelVaroquaux > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn >
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