Version 1.6

Legend for changelogs

• Major Feature something big that you couldn’t do before.

• Feature something that you couldn’t do before.

• Efficiency an existing feature now may not require as much computation or memory.

• Enhancement a miscellaneous minor improvement.

• Fix something that previously didn’t work as documented – or according to reasonable expectations – should now work.

• API Change you will need to change your code to have the same effect in the future; or a feature will be removed in the future.

Version 1.6.0

In Development

Support for Array API

Additional estimators and functions have been updated to include support for all Array API compliant inputs.

See Array API support (experimental) for more details.

Functions:

• sklearn.metrics.mean_tweedie_deviance now supports Array API compatible inputs. #28106 by Thomas Li;

• sklearn.metrics.mean_absolute_error #27736 by Edoardo Abati;

• sklearn.metrics.pairwise.cosine_similarity #29014 by Edoardo Abati.

Classes:

• preprocessing.LabelEncoder now supports Array API compatible inputs. #27381 by Omar Salman.

Metadata Routing

The following models now support metadata routing in one or more of their methods. Refer to the Metadata Routing User Guide for more details.

• Feature model_selection.learning_curve now supports metadata routing for the fit method of its estimator and for its underlying CV splitter and scorer. #28975 by Stefanie Senger.

• Feature ensemble.StackingClassifier and ensemble.StackingRegressor now support metadata routing and pass **fit_params to the underlying estimators via their fit methods. #28701 by Stefanie Senger.

Changelog

Thanks to everyone who has contributed to the maintenance and improvement of the project since version 1.5, including:

TODO: update at the time of the release.