Version 1.5

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 1.5.0

In Development

Support for building with Meson

Meson is now supported as a build backend, see Building with Meson for more details.

#28040 by Loïc Estève

TODO Fill more details before the 1.5 release, when the Meson story has settled down.

Changelog

sklearn.compose

• Feature A fitted compose.ColumnTransformer now implements __getitem__ which returns the fitted transformers by name. #27990 by Thomas Fan.

sklearn.dummy

• Enhancement dummy.DummyClassifier and dummy.DummyRegressor now have the n_features_in_ and feature_names_in_ attributes after fit. #27937 by Marco vd Boom.

sklearn.ensemble

• Efficiency Improves runtime of predict of ensemble.HistGradientBoostingClassifier by avoiding to call predict_proba. #27844 by Christian Lorentzen.

sklearn.feature_extraction

• Efficiency feature_extraction.text.TfidfTransformer is 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.

• Enhancement feature_extraction.text.TfidfTransformer now preserves the data type of the input matrix if it is np.float64 or np.float32. #28136 by Guillaume Lemaitre.

sklearn.feature_selection

• Enhancement feature_selection.mutual_info_regression and feature_selection.mutual_info_classif now support n_jobs parameter. #28085 by Neto Menoci and Florin Andrei.

sklearn.impute

• Enhancement impute.SimpleImputer now supports custom strategies by passing a function in place of a strategy name. #28053 by Mark Elliot.

sklearn.metrics

• Efficiency Improve efficiency of functions brier_score_loss, calibration_curve, det_curve, precision_recall_curve, roc_curve when pos_label argument is specified. Also improve efficiency of methods from_estimator and from_predictions in RocCurveDisplay, PrecisionRecallDisplay, DetCurveDisplay, CalibrationDisplay. #28051 by Pierre de Fréminville.

sklearn.model_selection

• Enhancement CV splitters that ignores the group parameter now raises a warning when groups are passed in to split. #28210 by

sklearn.utils

• Enhancement utils.metaestimators.available_if now reraises the error from the check function as the cause of the AttributeError. #28198 by Thomas Fan.

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.