v1.4.rst

.. currentmodule:: sklearn

Version 1.4.0

In Development

Changed models

The following estimators and functions, when fit with the same data and parameters, may produce different models from the previous version. This often occurs due to changes in the modelling logic (bug fixes or enhancements), or in random sampling procedures.

• |Fix| The initialization of :class:`mixture.GaussianMixture` from user-provided precisions_init for covariance_type of full or tied was not correct, and has been fixed. :pr:`26416` by :user:`Yang Tao <mchikyt3>`.
• |Fix| Ridge models with solver='sparse_cg' may have slightly different results with scipy>=1.12, because of an underlying change in the scipy solver (see scipy#18488 for more details) :pr:`26814` by :user:`Loïc Estève <lesteve>`

Changes impacting all modules

• |Enhancement| All estimators now recognizes the column names from any dataframe that adopts the DataFrame Interchange Protocol. Dataframes that return a correct representation through np.asarray(df) is expected to work with our estimators and functions. :pr:`26464` by `Thomas Fan`_.

Changelog

:mod:`sklearn.base`

• |Enhancement| :meth:`base.ClusterMixin.fit_predict` and :meth:`base.OutlierMixin.fit_predict` now accept **kwargs which are passed to the fit method of the the estimator. :pr:`26506` by `Adrin Jalali`_.
• |Enhancement| :meth:`base.TransformerMixin.fit_transform` and :meth:`base.OutlierMixin.fit_predict` now raise a warning if transform / predict consume metadata, but no custom fit_transform / fit_predict is defined in the class inheriting from them correspondingly. :pr:`26831` by `Adrin Jalali`_.
• |Enhancement| :func:`base.clone` now supports dict as input and creates a copy. :pr:`26786` by `Adrin Jalali`_.
• |API|:func:`~utils.metadata_routing.process_routing` now has a different signature. The first two (the object and the method) are positional only, and all metadata are passed as keyword arguments. :pr:`26909` by `Adrin Jalali`_.

:mod:`sklearn.cluster`

• |API| : kdtree and balltree values are now deprecated and are renamed as kd_tree and ball_tree respectively for the algorithm parameter of :class:`cluster.HDBSCAN` ensuring consistency in naming convention. kdtree and balltree values will be removed in 1.6. :pr:`26744` by :user:`Shreesha Kumar Bhat <Shreesha3112>`.

:mod:`sklearn.cross_decomposition`

• |Fix| :class:`cross_decomposition.PLSRegression` now automatically ravels the output of predict if fitted with one dimensional y. :pr:`26602` by :user:`Yao Xiao <Charlie-XIAO>`.

:mod:`sklearn.decomposition`

• |Enhancement| An "auto" option was added to the n_components parameter of :func:`decomposition.non_negative_factorization`, :class:`decomposition.NMF` and :class:`decomposition.MiniBatchNMF` to automatically infer the number of components from W or H shapes when using a custom initialization. The default value of this parameter will change from None to auto in version 1.6. :pr:`26634` by :user:`Alexandre Landeau <AlexL>` and :user:`Alexandre Vigny <avigny>`.
• |Enhancement| :class:`decomposition.PCA` now supports the Array API for the full and randomized solvers (with QR power iterations). See :ref:`array_api` for more details. :pr:`26315` and :pr:`27098` by :user:`Mateusz Sokół <mtsokol>`, :user:`Olivier Grisel <ogrisel>` and :user:` Edoardo Abati <EdAbati>`.
• |Enhancement| :func:`decomposition.non_negative_factorization`, :class:`decomposition.NMF`, and :class:`decomposition.MiniBatchNMF` now support :class:`scipy.sparse.sparray` subclasses. :pr:`27100` by :user:`Isaac Virshup <ivirshup>`.

:mod:`sklearn.ensemble`

• |MajorFeature| :class:`ensemble.RandomForestClassifier` and :class:`ensemble.RandomForestRegressor` support missing values when the criterion is gini, entropy, or log_loss, for classification or squared_error, friedman_mse, or poisson for regression. :pr:`26391` by `Thomas Fan`_.
• |Feature| :class:`ensemble.RandomForestClassifier`, :class:`ensemble.RandomForestRegressor`, :class:`ensemble.ExtraTreesClassifier` and :class:`ensemble.ExtraTreesRegressor` now support monotonic constraints, useful when features are supposed to have a positive/negative effect on the target. Missing values in the train data and multi-output targets are not supported. :pr:`13649` by :user:`Samuel Ronsin <samronsin>`, initiated by :user:`Patrick O'Reilly <pat-oreilly>`.
• |Efficiency| Improves runtime and memory usage for :class:`ensemble.GradientBoostingClassifier` and :class:`ensemble.GradientBoostingRegressor` when trained on sparse data. :pr:`26957` by `Thomas Fan`_.

:mod:`sklearn.feature_selection`

• |Fix| :func:`feature_selection.mutual_info_regression` now correctly computes the result when X is of integer dtype. :pr:`26748` by :user:`Yao Xiao <Charlie-XIAO>`.

:mod:`sklearn.linear_model`

• |Enhancement| :class:`linear_model.LogisticRegressionCV` now supports metadata routing. :meth:`linear_model.LogisticRegressionCV.fit` now accepts **params which are passed to the underlying splitter and scorer. :meth:`linear_model.LogisticRegressionCV.score` now accepts **score_params which are passed to the underlying scorer. :pr:`26525` by :user:`Omar Salman <OmarManzoor>`.

:mod:`sklearn.pipeline`

• |Feature| :class:`pipeline.Pipeline` now supports metadata routing according to :ref:`metadata routing user guide <metadata_routing>`. :pr:`26789` by `Adrin Jalali`_.

:mod:`sklearn.model_selection`

• |Fix| :class:`model_selection.GridSearchCV`, :class:`model_selection.RandomizedSearchCV`, and :class:`model_selection.HalvingGridSearchCV` now don't change the given object in the parameter grid if it's an estimator. :pr:`26786` by `Adrin Jalali`_.
• |Feature| :func:`~model_selection.cross_validate`, :func:`~model_selection.cross_val_score`, and :func:`~model_selection.cross_val_predict` now support metadata routing. The metadata are routed to the estimator's fit, the scorer, and the CV splitter's split. The metadata is accepted via the new params parameter. fit_params is deprecated and will be removed in version 1.6. groups parameter is also not accepted as a separate argument when metadata routing is enabled and should be passed via the params parameter. :pr:`26896` by `Adrin Jalali`_.
• |Enhancement| :func:`sklearn.model_selection.train_test_split` now supports Array API compatible inputs. :pr:`26855` by `Tim Head`_.

:mod:`sklearn.neighbors`

• |Efficiency| :meth:`sklearn.neighbors.KNeighborsRegressor.predict` and :meth:`sklearn.neighbors.KNeighborsRegressor.predict_proba` now efficiently support pairs of dense and sparse datasets. :pr:`27018` by :user:`Julien Jerphanion <jjerphan>`.
• |Fix| Neighbors based estimators now correctly work when metric="minkowski" and the metric parameter p is in the range 0 < p < 1, regardless of the dtype of X. :pr:`26760` by :user:`Shreesha Kumar Bhat <Shreesha3112>`.

:mod:`sklearn.preprocessing`

• |Efficiency| :class:`preprocessing.OrdinalEncoder` avoids calculating missing indices twice to improve efficiency. :pr:`27017` by :user:`Xuefeng Xu <xuefeng-xu>`.
• |Fix| :class:`preprocessing.OneHotEncoder` shows a more informative error message when sparse_output=True and the output is configured to be pandas. :pr:`26931` by `Thomas Fan`_.
• |MajorFeature| :class:`preprocessing.MinMaxScaler` and :class:`preprocessing.MaxAbsScaler` now supports the Array API. Array API support is considered experimental and might evolve without being subject to our usual rolling deprecation cycle policy. See :ref:`array_api` for more details. :pr:`26243` by `Tim Head`_ and :pr:`27110` by :user:`Edoardo Abati <EdAbati>`.

:mod:`sklearn.tree`

• |Feature| :class:`tree.DecisionTreeClassifier`, :class:`tree.DecisionTreeRegressor`, :class:`tree.ExtraTreeClassifier` and :class:`tree.ExtraTreeRegressor` now support monotonic constraints, useful when features are supposed to have a positive/negative effect on the target. Missing values in the train data and multi-output targets are not supported. :pr:`13649` by :user:`Samuel Ronsin <samronsin>`, initiated by :user:`Patrick O'Reilly <pat-oreilly>`.

:mod:`sklearn.neighbors`

• |API| :class:`neighbors.KNeighborsRegressor` now accepts :class:`metric.DistanceMetric` objects directly via the metric keyword argument allowing for the use of accelerated third-party :class:`metric.DistanceMetric` objects. :pr:`26267` by :user:`Meekail Zain <micky774>`

:mod:`sklearn.metrics`

• |Efficiency| Computing pairwise distances via :class:`metrics.DistanceMetric` for CSR × CSR, Dense × CSR, and CSR × Dense datasets is now 1.5x faster. :pr:`26765` by :user:`Meekail Zain <micky774>`
• |Efficiency| Computing distances via :class:`metrics.DistanceMetric` for CSR × CSR, Dense × CSR, and CSR × Dense now uses ~50% less memory, and outputs distances in the same dtype as the provided data. :pr:`27006` by :user:`Meekail Zain <micky774>`

:mod:`sklearn.utils`

• |Enhancement| :func:`sklearn.utils.estimator_html_repr` dynamically adapts diagram colors based on the browser's prefers-color-scheme, providing improved adaptability to dark mode environments. :pr:`26862` by :user:`Andrew Goh Yisheng <9y5>`, `Thomas Fan`_, `Adrin Jalali`_.
• |Enhancement| :class:`~utils.metadata_routing.MetadataRequest` and :class:`~utils.metadata_routing.MetadataRouter` now have a consumes method which can be used to check whether a given set of parameters would be consumed. :pr:`26831` by `Adrin Jalali`_.

Code and Documentation Contributors

Thanks to everyone who has contributed to the maintenance and improvement of the project since version 1.3, including:

TODO: update at the time of the release.