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.
Support for building with Meson¶
Meson is now supported as a build backend, see Building with Meson for more details.
TODO Fill more details before the 1.5 release, when the Meson story has settled down.
The following models now support metadata routing in one or more or their methods. Refer to the Metadata Routing User Guide for more details.
ensemble.BaggingRegressornow support metadata routing. The fit methods now accept
**fit_paramswhich are passed to the underlying estimators via their
fitmethods. #28432 by Adam Li and Benjamin Bossan.
ensemble.HistGradientBoostingRegressorare now a tiny bit faster by pre-sorting the data before finding the thresholds for binning. #28102 by Christian Lorentzen.
feature_extraction.text.TfidfTransformeris now faster and more memory-efficient by using a NumPy vector instead of a sparse matrix for storing the inverse document frequency. #18843 by Paolo Montesel.
Efficiency Improve efficiency of functions
pos_labelargument is specified. Also improve efficiency of methods
CalibrationDisplay. #28051 by Pierre de Fréminville.
pipeline.FeatureUnioncan now use the
get_feature_names_outwill prefix all feature names with the name of the transformer that generated that feature. If
get_feature_names_outwill not prefix any feature names and will error if feature names are not unique. #25991 by Jiawei Zhang.
Code and documentation contributors
Thanks to everyone who has contributed to the maintenance and improvement of the project since version 1.4, including:
TODO: update at the time of the release.