Version 1.9#

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 1.9.dev0#

January 2026

Enhancement pipeline.Pipeline, pipeline.FeatureUnion and compose.ColumnTransformer now raise a clearer error message when an estimator class is passed instead of an instance. By Anne Beyer #32888
Fix Raise ValueError when sample_weight contains only zero values to prevent meaningless input data during fitting. This change applies to all estimators that support the parameter sample_weight. This change also affects metrics that validate sample weights. By Lucy Liu and John Hendricks. #32212
Fix Some parameter descriptions in the HTML representation of estimators were not properly escaped, which could lead to malformed HTML if the description contains characters like < or >. By Olivier Grisel. #32942

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

Feature sklearn.metrics.d2_absolute_error_score and sklearn.metrics.d2_pinball_score now support array API compatible inputs. By Virgil Chan. #31671
Feature sklearn.metrics.pairwise.paired_manhattan_distances now supports array API compatible inputs. By Bharat Raghunathan. #32979
Enhancement kernel_approximation.Nystroem now supports array API compatible inputs. By Emily Chen #29661
Fix Fixed a bug that would cause Cython-based estimators to fail when fit on NumPy inputs when setting sklearn.set_config(array_api_dispatch=True). By Olivier Grisel. #32846
Fix Fixes how pos_label is inferred when pos_label is set to None, in sklearn.metrics.brier_score_loss and sklearn.metrics.d2_brier_score. By Lucy Liu. #32923

Fix The dotted line for compose.ColumnTransformer in its HTML display now includes only its elements. The behaviour when a remainder is used, has also been corrected. By Dea María Léon #32713

Fix ensemble.RandomForestClassifier, ensemble.RandomForestRegressor, ensemble.ExtraTreesClassifier and ensemble.ExtraTreesRegressor now use sample_weight to draw the samples instead of forwarding them multiplied by a uniformly sampled mask to the underlying estimators. Furthermore, when max_samples is a float, it is now interpreted as a fraction of sample_weight.sum() instead of X.shape[0]. As sampling is done with replacement, a float max_samples greater than 1.0 is now allowed, as well as an integer max_samples greater then X.shape[0]. The default max_samples=None draws X.shape[0] samples, irrespective of sample_weight. By Antoine Baker. #31529
Fix Both ensemble.GradientBoostingRegressor and ensemble.GradientBoostingClassifier with the default "friedman_mse" criterion were computing impurity values with an incorrect scaling, leading to unexpected trees in some cases. The implementation now uses "squared_error", which is exactly equivalent to "friedman_mse" up to floating-point error discrepancies but computes correct impurity values. By Arthur Lacote. #32708
API Change The criterion parameter is now deprecated for classes ensemble.GradientBoostingRegressor and ensemble.GradientBoostingClassifier, as both options ("friedman_mse" and "squared_error") were producing the same results, up to floating-point rounding discrepancies and a bug in "friedman_mse". By Arthur Lacote #32708

Enhancement linear_model.ElasticNet, linear_model.ElasticNetCV and linear_model.enet_path now are able to fit Ridge regression, i.e. setting l1_ratio=0. Before this PR, the stopping criterion was a formulation of the dual gap that breaks down for l1_ratio=0. Now, an alternative dual gap formulation is used for this setting. This reduces the noise of raised warnings. By Christian Lorentzen. #32845
Fix linear_model.LassoCV and linear_model.ElasticNetCV now take the positive parameter into account to compute the maximum alpha parameter, where all coefficients are zero. This impacts the search grid for the internally tuned alpha hyper-parameter stored in the attribute alphas_. By Junteng Li #32768
Fix Correct the formulation of alpha within linear_model.SGDOneClassSVM. The corrected value is alpha = nu instead of alpha = nu / 2. Note: This might result in changed values for the fitted attributes like coef_ and offset_ as well as the predictions made using this class. By Omar Salman. #32778

Fix metrics.d2_pinball_score and metrics.d2_absolute_error_score now always use the "averaged_inverted_cdf" quantile method, both with and without sample weights. Previously, the "linear" quantile method was used only for the unweighted case leading the surprising discrepancies when comparing the results with unit weights. Note that all quantile interpolation methods are asymptotically equivalent in the large sample limit, but this fix can cause score value changes on small evaluation sets (without weights). By Virgil Chan. #31671

Fix Raise more informative error when fitting NuSVR with all zero sample weights. By Lucy Liu and John Hendricks. #32212

API Change criterion="friedman_mse" is now deprecated. This criterion was intended for gradient boosting but was incorrectly implemented in scikit-learn’s trees and was actually behaving identically to criterion="squared_error". Use criterion="squared_error" instead. This affects: - tree.DecisionTreeRegressor - tree.ExtraTreeRegressor - ensemble.RandomForestRegressor - ensemble.ExtraTreesRegressor By Arthur Lacote #32708

Fix The parameter table in the HTML representation of all scikit-learn estimators inheritiging from base.BaseEstimator, displays each parameter documentation as a tooltip. The last tooltip of a parameter in the last table of any HTML representation was partially hidden. This issue has been fixed. By Dea María Léon #32887

Code and documentation contributors

Thanks to everyone who has contributed to the maintenance and improvement of the project since version 1.8, including:

TODO: update at the time of the release.