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ReStructuredText
651 lines
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ReStructuredText
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.. include:: _contributors.rst
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.. currentmodule:: sklearn
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.. _release_notes_1_5:
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===========
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Version 1.5
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===========
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For a short description of the main highlights of the release, please refer to
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:ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_5_0.py`.
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.. include:: changelog_legend.inc
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.. _changes_1_5_1:
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Version 1.5.1
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=============
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**July 2024**
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Changes impacting many modules
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------------------------------
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- |Fix| Fixed a regression in the validation of the input data of all estimators where
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an unexpected error was raised when passing a DataFrame backed by a read-only buffer.
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:pr:`29018` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
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- |Fix| Fixed a regression causing a dead-lock at import time in some settings.
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:pr:`29235` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
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Changelog
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---------
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:mod:`sklearn.compose`
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......................
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- |Efficiency| Fix a performance regression in :class:`compose.ColumnTransformer`
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where the full input data was copied for each transformer when `n_jobs > 1`.
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:pr:`29330` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
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:mod:`sklearn.metrics`
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......................
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- |Fix| Fix a regression in :func:`metrics.r2_score`. Passing torch CPU tensors
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with array API dispatched disabled would complain about non-CPU devices
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instead of implicitly converting those inputs as regular NumPy arrays.
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:pr:`29119` by :user:`Olivier Grisel`.
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- |Fix| Fix a regression in :func:`metrics.accuracy_score` and in
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:func:`metrics.zero_one_loss` causing an error for Array API dispatch with multilabel
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inputs.
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:pr:`29269` by :user:`Yaroslav Korobko <Tialo>` and
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:pr:`29336` by :user:`Edoardo Abati <EdAbati>`.
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:mod:`sklearn.model_selection`
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..............................
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- |Fix| Fix a regression in :class:`model_selection.GridSearchCV` for parameter
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grids that have heterogeneous parameter values.
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:pr:`29078` by :user:`Loïc Estève <lesteve>`.
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- |Fix| Fix a regression in :class:`model_selection.GridSearchCV` for parameter
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grids that have estimators as parameter values.
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:pr:`29179` by :user:`Marco Gorelli<MarcoGorelli>`.
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- |Fix| Fix a regression in :class:`model_selection.GridSearchCV` for parameter
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grids that have arrays of different sizes as parameter values.
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:pr:`29314` by :user:`Marco Gorelli<MarcoGorelli>`.
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:mod:`sklearn.tree`
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...................
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- |Fix| Fix an issue in :func:`tree.export_graphviz` and :func:`tree.plot_tree`
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that could potentially result in exception or wrong results on 32bit OSes.
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:pr:`29327` by :user:`Loïc Estève<lesteve>`.
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:mod:`sklearn.utils`
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....................
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- |API| :func:`utils.validation.check_array` has a new parameter, `force_writeable`, to
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control the writeability of the output array. If set to `True`, the output array will
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be guaranteed to be writeable and a copy will be made if the input array is read-only.
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If set to `False`, no guarantee is made about the writeability of the output array.
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:pr:`29018` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
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.. _changes_1_5:
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Version 1.5.0
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=============
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**May 2024**
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Security
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--------
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- |Fix| :class:`feature_extraction.text.CountVectorizer` and
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:class:`feature_extraction.text.TfidfVectorizer` no longer store discarded
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tokens from the training set in their `stop_words_` attribute. This attribute
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would hold too frequent (above `max_df`) but also too rare tokens (below
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`min_df`). This fixes a potential security issue (data leak) if the discarded
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rare tokens hold sensitive information from the training set without the
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model developer's knowledge.
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Note: users of those classes are encouraged to either retrain their pipelines
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with the new scikit-learn version or to manually clear the `stop_words_`
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attribute from previously trained instances of those transformers. This
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attribute was designed only for model inspection purposes and has no impact
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on the behavior of the transformers.
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:pr:`28823` by :user:`Olivier Grisel <ogrisel>`.
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Changed models
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--------------
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- |Efficiency| The subsampling in :class:`preprocessing.QuantileTransformer` is now
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more efficient for dense arrays but the fitted quantiles and the results of
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`transform` may be slightly different than before (keeping the same statistical
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properties).
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:pr:`27344` by :user:`Xuefeng Xu <xuefeng-xu>`.
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- |Enhancement| :class:`decomposition.PCA`, :class:`decomposition.SparsePCA`
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and :class:`decomposition.TruncatedSVD` now set the sign of the `components_`
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attribute based on the component values instead of using the transformed data
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as reference. This change is needed to be able to offer consistent component
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signs across all `PCA` solvers, including the new
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`svd_solver="covariance_eigh"` option introduced in this release.
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Changes impacting many modules
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------------------------------
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- |Fix| Raise `ValueError` with an informative error message when passing 1D
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sparse arrays to methods that expect 2D sparse inputs.
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:pr:`28988` by :user:`Olivier Grisel <ogrisel>`.
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- |API| The name of the input of the `inverse_transform` method of estimators has been
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standardized to `X`. As a consequence, `Xt` is deprecated and will be removed in
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version 1.7 in the following estimators: :class:`cluster.FeatureAgglomeration`,
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:class:`decomposition.MiniBatchNMF`, :class:`decomposition.NMF`,
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:class:`model_selection.GridSearchCV`, :class:`model_selection.RandomizedSearchCV`,
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:class:`pipeline.Pipeline` and :class:`preprocessing.KBinsDiscretizer`.
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:pr:`28756` by :user:`Will Dean <wd60622>`.
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Support for Array API
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---------------------
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Additional estimators and functions have been updated to include support for all
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`Array API <https://data-apis.org/array-api/latest/>`_ compliant inputs.
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See :ref:`array_api` for more details.
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**Functions:**
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- :func:`sklearn.metrics.r2_score` now supports Array API compliant inputs.
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:pr:`27904` by :user:`Eric Lindgren <elindgren>`, :user:`Franck Charras <fcharras>`,
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:user:`Olivier Grisel <ogrisel>` and :user:`Tim Head <betatim>`.
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**Classes:**
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- :class:`linear_model.Ridge` now supports the Array API for the `svd` solver.
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See :ref:`array_api` for more details.
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:pr:`27800` by :user:`Franck Charras <fcharras>`, :user:`Olivier Grisel <ogrisel>`
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and :user:`Tim Head <betatim>`.
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Support for building with Meson
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-------------------------------
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From scikit-learn 1.5 onwards, Meson is the main supported way to build
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scikit-learn, see :ref:`Building from source <install_bleeding_edge>` for more
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details.
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Unless we discover a major blocker, setuptools support will be dropped in
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scikit-learn 1.6. The 1.5.x releases will support building scikit-learn with
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setuptools.
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Meson support for building scikit-learn was added in :pr:`28040` by
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:user:`Loïc Estève <lesteve>`
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Metadata Routing
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----------------
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The following models now support metadata routing in one or more or their
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methods. Refer to the :ref:`Metadata Routing User Guide <metadata_routing>` for
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more details.
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- |Feature| :class:`impute.IterativeImputer` now supports metadata routing in
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its `fit` method. :pr:`28187` by :user:`Stefanie Senger <StefanieSenger>`.
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- |Feature| :class:`ensemble.BaggingClassifier` and :class:`ensemble.BaggingRegressor`
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now support metadata routing. The fit methods now
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accept ``**fit_params`` which are passed to the underlying estimators
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via their `fit` methods.
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:pr:`28432` by :user:`Adam Li <adam2392>` and
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:user:`Benjamin Bossan <BenjaminBossan>`.
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- |Feature| :class:`linear_model.RidgeCV` and
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:class:`linear_model.RidgeClassifierCV` now support metadata routing in
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their `fit` method and route metadata to the underlying
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:class:`model_selection.GridSearchCV` object or the underlying scorer.
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:pr:`27560` by :user:`Omar Salman <OmarManzoor>`.
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- |Feature| :class:`GraphicalLassoCV` now supports metadata routing in it's
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`fit` method and routes metadata to the CV splitter.
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:pr:`27566` by :user:`Omar Salman <OmarManzoor>`.
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- |Feature| :class:`linear_model.RANSACRegressor` now supports metadata routing
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in its ``fit``, ``score`` and ``predict`` methods and route metadata to its
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underlying estimator's' ``fit``, ``score`` and ``predict`` methods.
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:pr:`28261` by :user:`Stefanie Senger <StefanieSenger>`.
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- |Feature| :class:`ensemble.VotingClassifier` and
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:class:`ensemble.VotingRegressor` now support metadata routing and pass
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``**fit_params`` to the underlying estimators via their `fit` methods.
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:pr:`27584` by :user:`Stefanie Senger <StefanieSenger>`.
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- |Feature| :class:`pipeline.FeatureUnion` now supports metadata routing in its
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``fit`` and ``fit_transform`` methods and route metadata to the underlying
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transformers' ``fit`` and ``fit_transform``.
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:pr:`28205` by :user:`Stefanie Senger <StefanieSenger>`.
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- |Fix| Fix an issue when resolving default routing requests set via class
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attributes.
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:pr:`28435` by `Adrin Jalali`_.
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- |Fix| Fix an issue when `set_{method}_request` methods are used as unbound
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methods, which can happen if one tries to decorate them.
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:pr:`28651` by `Adrin Jalali`_.
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- |FIX| Prevent a `RecursionError` when estimators with the default `scoring`
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param (`None`) route metadata.
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:pr:`28712` by :user:`Stefanie Senger <StefanieSenger>`.
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Changelog
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---------
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..
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Entries should be grouped by module (in alphabetic order) and prefixed with
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one of the labels: |MajorFeature|, |Feature|, |Efficiency|, |Enhancement|,
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|Fix| or |API| (see whats_new.rst for descriptions).
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Entries should be ordered by those labels (e.g. |Fix| after |Efficiency|).
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Changes not specific to a module should be listed under *Multiple Modules*
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or *Miscellaneous*.
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Entries should end with:
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:pr:`123456` by :user:`Joe Bloggs <joeongithub>`.
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where 123455 is the *pull request* number, not the issue number.
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:mod:`sklearn.calibration`
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..........................
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- |Fix| Fixed a regression in :class:`calibration.CalibratedClassifierCV` where
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an error was wrongly raised with string targets.
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:pr:`28843` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
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:mod:`sklearn.cluster`
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......................
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- |Fix| The :class:`cluster.MeanShift` class now properly converges for constant data.
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:pr:`28951` by :user:`Akihiro Kuno <akikuno>`.
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- |FIX| Create copy of precomputed sparse matrix within the `fit` method of
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:class:`~cluster.OPTICS` to avoid in-place modification of the sparse matrix.
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:pr:`28491` by :user:`Thanh Lam Dang <lamdang2k>`.
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- |Fix| :class:`cluster.HDBSCAN` now supports all metrics supported by
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:func:`sklearn.metrics.pairwise_distances` when `algorithm="brute"` or `"auto"`.
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:pr:`28664` by :user:`Manideep Yenugula <myenugula>`.
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:mod:`sklearn.compose`
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|||
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......................
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- |Feature| A fitted :class:`compose.ColumnTransformer` now implements `__getitem__`
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which returns the fitted transformers by name. :pr:`27990` by `Thomas Fan`_.
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- |Enhancement| :class:`compose.TransformedTargetRegressor` now raises an error in `fit`
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if only `inverse_func` is provided without `func` (that would default to identity)
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being explicitly set as well.
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:pr:`28483` by :user:`Stefanie Senger <StefanieSenger>`.
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- |Enhancement| :class:`compose.ColumnTransformer` can now expose the "remainder"
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columns in the fitted `transformers_` attribute as column names or boolean
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masks, rather than column indices.
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:pr:`27657` by :user:`Jérôme Dockès <jeromedockes>`.
|
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- |Fix| Fixed an bug in :class:`compose.ColumnTransformer` with `n_jobs > 1`, where the
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intermediate selected columns were passed to the transformers as read-only arrays.
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:pr:`28822` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
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:mod:`sklearn.cross_decomposition`
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..................................
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- |Fix| The `coef_` fitted attribute of :class:`cross_decomposition.PLSRegression`
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now takes into account both the scale of `X` and `Y` when `scale=True`. Note that
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the previous predicted values were not affected by this bug.
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:pr:`28612` by :user:`Guillaume Lemaitre <glemaitre>`.
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- |API| Deprecates `Y` in favor of `y` in the methods fit, transform and
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inverse_transform of:
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:class:`cross_decomposition.PLSRegression`.
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:class:`cross_decomposition.PLSCanonical`,
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:class:`cross_decomposition.CCA`,
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and :class:`cross_decomposition.PLSSVD`.
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`Y` will be removed in version 1.7.
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:pr:`28604` by :user:`David Leon <davidleon123>`.
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|
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:mod:`sklearn.datasets`
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.......................
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- |Enhancement| Adds optional arguments `n_retries` and `delay` to functions
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:func:`datasets.fetch_20newsgroups`,
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:func:`datasets.fetch_20newsgroups_vectorized`,
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:func:`datasets.fetch_california_housing`,
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:func:`datasets.fetch_covtype`,
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:func:`datasets.fetch_kddcup99`,
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:func:`datasets.fetch_lfw_pairs`,
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:func:`datasets.fetch_lfw_people`,
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:func:`datasets.fetch_olivetti_faces`,
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:func:`datasets.fetch_rcv1`,
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and :func:`datasets.fetch_species_distributions`.
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|
By default, the functions will retry up to 3 times in case of network failures.
|
|||
|
|
:pr:`28160` by :user:`Zhehao Liu <MaxwellLZH>` and
|
|||
|
|
:user:`Filip Karlo Došilović <fkdosilovic>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.decomposition`
|
|||
|
|
............................
|
|||
|
|
|
|||
|
|
- |Efficiency| :class:`decomposition.PCA` with `svd_solver="full"` now assigns
|
|||
|
|
a contiguous `components_` attribute instead of an non-contiguous slice of
|
|||
|
|
the singular vectors. When `n_components << n_features`, this can save some
|
|||
|
|
memory and, more importantly, help speed-up subsequent calls to the `transform`
|
|||
|
|
method by more than an order of magnitude by leveraging cache locality of
|
|||
|
|
BLAS GEMM on contiguous arrays.
|
|||
|
|
:pr:`27491` by :user:`Olivier Grisel <ogrisel>`.
|
|||
|
|
|
|||
|
|
- |Enhancement| :class:`~decomposition.PCA` now automatically selects the ARPACK solver
|
|||
|
|
for sparse inputs when `svd_solver="auto"` instead of raising an error.
|
|||
|
|
:pr:`28498` by :user:`Thanh Lam Dang <lamdang2k>`.
|
|||
|
|
|
|||
|
|
- |Enhancement| :class:`decomposition.PCA` now supports a new solver option
|
|||
|
|
named `svd_solver="covariance_eigh"` which offers an order of magnitude
|
|||
|
|
speed-up and reduced memory usage for datasets with a large number of data
|
|||
|
|
points and a small number of features (say, `n_samples >> 1000 >
|
|||
|
|
n_features`). The `svd_solver="auto"` option has been updated to use the new
|
|||
|
|
solver automatically for such datasets. This solver also accepts sparse input
|
|||
|
|
data.
|
|||
|
|
:pr:`27491` by :user:`Olivier Grisel <ogrisel>`.
|
|||
|
|
|
|||
|
|
- |Fix| :class:`decomposition.PCA` fit with `svd_solver="arpack"`,
|
|||
|
|
`whiten=True` and a value for `n_components` that is larger than the rank of
|
|||
|
|
the training set, no longer returns infinite values when transforming
|
|||
|
|
hold-out data.
|
|||
|
|
:pr:`27491` by :user:`Olivier Grisel <ogrisel>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.dummy`
|
|||
|
|
....................
|
|||
|
|
|
|||
|
|
- |Enhancement| :class:`dummy.DummyClassifier` and :class:`dummy.DummyRegressor` now
|
|||
|
|
have the `n_features_in_` and `feature_names_in_` attributes after `fit`.
|
|||
|
|
:pr:`27937` by :user:`Marco vd Boom <tvdboom>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.ensemble`
|
|||
|
|
.......................
|
|||
|
|
|
|||
|
|
- |Efficiency| Improves runtime of `predict` of
|
|||
|
|
:class:`ensemble.HistGradientBoostingClassifier` by avoiding to call `predict_proba`.
|
|||
|
|
:pr:`27844` by :user:`Christian Lorentzen <lorentzenchr>`.
|
|||
|
|
|
|||
|
|
- |Efficiency| :class:`ensemble.HistGradientBoostingClassifier` and
|
|||
|
|
:class:`ensemble.HistGradientBoostingRegressor` are now a tiny bit faster by
|
|||
|
|
pre-sorting the data before finding the thresholds for binning.
|
|||
|
|
:pr:`28102` by :user:`Christian Lorentzen <lorentzenchr>`.
|
|||
|
|
|
|||
|
|
- |Fix| Fixes a bug in :class:`ensemble.HistGradientBoostingClassifier` and
|
|||
|
|
:class:`ensemble.HistGradientBoostingRegressor` when `monotonic_cst` is specified
|
|||
|
|
for non-categorical features.
|
|||
|
|
:pr:`28925` by :user:`Xiao Yuan <yuanx749>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.feature_extraction`
|
|||
|
|
.................................
|
|||
|
|
|
|||
|
|
- |Efficiency| :class:`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.
|
|||
|
|
:pr:`18843` by :user:`Paolo Montesel <thebabush>`.
|
|||
|
|
|
|||
|
|
- |Enhancement| :class:`feature_extraction.text.TfidfTransformer` now preserves
|
|||
|
|
the data type of the input matrix if it is `np.float64` or `np.float32`.
|
|||
|
|
:pr:`28136` by :user:`Guillaume Lemaitre <glemaitre>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.feature_selection`
|
|||
|
|
................................
|
|||
|
|
|
|||
|
|
- |Enhancement| :func:`feature_selection.mutual_info_regression` and
|
|||
|
|
:func:`feature_selection.mutual_info_classif` now support `n_jobs` parameter.
|
|||
|
|
:pr:`28085` by :user:`Neto Menoci <netomenoci>` and
|
|||
|
|
:user:`Florin Andrei <FlorinAndrei>`.
|
|||
|
|
|
|||
|
|
- |Enhancement| The `cv_results_` attribute of :class:`feature_selection.RFECV` has
|
|||
|
|
a new key, `n_features`, containing an array with the number of features selected
|
|||
|
|
at each step.
|
|||
|
|
:pr:`28670` by :user:`Miguel Silva <miguelcsilva>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.impute`
|
|||
|
|
.....................
|
|||
|
|
|
|||
|
|
- |Enhancement| :class:`impute.SimpleImputer` now supports custom strategies
|
|||
|
|
by passing a function in place of a strategy name.
|
|||
|
|
:pr:`28053` by :user:`Mark Elliot <mark-thm>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.inspection`
|
|||
|
|
.........................
|
|||
|
|
|
|||
|
|
- |Fix| :meth:`inspection.DecisionBoundaryDisplay.from_estimator` no longer
|
|||
|
|
warns about missing feature names when provided a `polars.DataFrame`.
|
|||
|
|
:pr:`28718` by :user:`Patrick Wang <patrickkwang>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.linear_model`
|
|||
|
|
...........................
|
|||
|
|
|
|||
|
|
- |Enhancement| Solver `"newton-cg"` in :class:`linear_model.LogisticRegression` and
|
|||
|
|
:class:`linear_model.LogisticRegressionCV` now emits information when `verbose` is
|
|||
|
|
set to positive values.
|
|||
|
|
:pr:`27526` by :user:`Christian Lorentzen <lorentzenchr>`.
|
|||
|
|
|
|||
|
|
- |Fix| :class:`linear_model.ElasticNet`, :class:`linear_model.ElasticNetCV`,
|
|||
|
|
:class:`linear_model.Lasso` and :class:`linear_model.LassoCV` now explicitly don't
|
|||
|
|
accept large sparse data formats.
|
|||
|
|
:pr:`27576` by :user:`Stefanie Senger <StefanieSenger>`.
|
|||
|
|
|
|||
|
|
- |Fix| :class:`linear_model.RidgeCV` and :class:`RidgeClassifierCV` correctly pass
|
|||
|
|
`sample_weight` to the underlying scorer when `cv` is None.
|
|||
|
|
:pr:`27560` by :user:`Omar Salman <OmarManzoor>`.
|
|||
|
|
|
|||
|
|
- |Fix| `n_nonzero_coefs_` attribute in :class:`linear_model.OrthogonalMatchingPursuit`
|
|||
|
|
will now always be `None` when `tol` is set, as `n_nonzero_coefs` is ignored in
|
|||
|
|
this case. :pr:`28557` by :user:`Lucy Liu <lucyleeow>`.
|
|||
|
|
|
|||
|
|
- |API| :class:`linear_model.RidgeCV` and :class:`linear_model.RidgeClassifierCV`
|
|||
|
|
will now allow `alpha=0` when `cv != None`, which is consistent with
|
|||
|
|
:class:`linear_model.Ridge` and :class:`linear_model.RidgeClassifier`.
|
|||
|
|
:pr:`28425` by :user:`Lucy Liu <lucyleeow>`.
|
|||
|
|
|
|||
|
|
- |API| Passing `average=0` to disable averaging is deprecated in
|
|||
|
|
:class:`linear_model.PassiveAggressiveClassifier`,
|
|||
|
|
:class:`linear_model.PassiveAggressiveRegressor`,
|
|||
|
|
:class:`linear_model.SGDClassifier`, :class:`linear_model.SGDRegressor` and
|
|||
|
|
:class:`linear_model.SGDOneClassSVM`. Pass `average=False` instead.
|
|||
|
|
:pr:`28582` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
|
|||
|
|
|
|||
|
|
- |API| Parameter `multi_class` was deprecated in
|
|||
|
|
:class:`linear_model.LogisticRegression` and
|
|||
|
|
:class:`linear_model.LogisticRegressionCV`. `multi_class` will be removed in 1.7,
|
|||
|
|
and internally, for 3 and more classes, it will always use multinomial.
|
|||
|
|
If you still want to use the one-vs-rest scheme, you can use
|
|||
|
|
`OneVsRestClassifier(LogisticRegression(..))`.
|
|||
|
|
:pr:`28703` by :user:`Christian Lorentzen <lorentzenchr>`.
|
|||
|
|
|
|||
|
|
- |API| `store_cv_values` and `cv_values_` are deprecated in favor of
|
|||
|
|
`store_cv_results` and `cv_results_` in `~linear_model.RidgeCV` and
|
|||
|
|
`~linear_model.RidgeClassifierCV`.
|
|||
|
|
:pr:`28915` by :user:`Lucy Liu <lucyleeow>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.manifold`
|
|||
|
|
.......................
|
|||
|
|
|
|||
|
|
- |API| Deprecates `n_iter` in favor of `max_iter` in :class:`manifold.TSNE`.
|
|||
|
|
`n_iter` will be removed in version 1.7. This makes :class:`manifold.TSNE`
|
|||
|
|
consistent with the rest of the estimators. :pr:`28471` by
|
|||
|
|
:user:`Lucy Liu <lucyleeow>`
|
|||
|
|
|
|||
|
|
:mod:`sklearn.metrics`
|
|||
|
|
......................
|
|||
|
|
|
|||
|
|
- |Feature| :func:`metrics.pairwise_distances` accepts calculating pairwise distances
|
|||
|
|
for non-numeric arrays as well. This is supported through custom metrics only.
|
|||
|
|
:pr:`27456` by :user:`Venkatachalam N <venkyyuvy>`, :user:`Kshitij Mathur <Kshitij68>`
|
|||
|
|
and :user:`Julian Libiseller-Egger <julibeg>`.
|
|||
|
|
|
|||
|
|
- |Feature| :func:`sklearn.metrics.check_scoring` now returns a multi-metric scorer
|
|||
|
|
when `scoring` as a `dict`, `set`, `tuple`, or `list`. :pr:`28360` by `Thomas Fan`_.
|
|||
|
|
|
|||
|
|
- |Feature| :func:`metrics.d2_log_loss_score` has been added which
|
|||
|
|
calculates the D^2 score for the log loss.
|
|||
|
|
:pr:`28351` by :user:`Omar Salman <OmarManzoor>`.
|
|||
|
|
|
|||
|
|
- |Efficiency| Improve efficiency of functions :func:`~metrics.brier_score_loss`,
|
|||
|
|
:func:`~calibration.calibration_curve`, :func:`~metrics.det_curve`,
|
|||
|
|
:func:`~metrics.precision_recall_curve`,
|
|||
|
|
:func:`~metrics.roc_curve` when `pos_label` argument is specified.
|
|||
|
|
Also improve efficiency of methods `from_estimator`
|
|||
|
|
and `from_predictions` in :class:`~metrics.RocCurveDisplay`,
|
|||
|
|
:class:`~metrics.PrecisionRecallDisplay`, :class:`~metrics.DetCurveDisplay`,
|
|||
|
|
:class:`~calibration.CalibrationDisplay`.
|
|||
|
|
:pr:`28051` by :user:`Pierre de Fréminville <pidefrem>`.
|
|||
|
|
|
|||
|
|
- |Fix|:class:`metrics.classification_report` now shows only accuracy and not
|
|||
|
|
micro-average when input is a subset of labels.
|
|||
|
|
:pr:`28399` by :user:`Vineet Joshi <vjoshi253>`.
|
|||
|
|
|
|||
|
|
- |Fix| Fix OpenBLAS 0.3.26 dead-lock on Windows in pairwise distances
|
|||
|
|
computation. This is likely to affect neighbor-based algorithms.
|
|||
|
|
:pr:`28692` by :user:`Loïc Estève <lesteve>`.
|
|||
|
|
|
|||
|
|
- |API| :func:`metrics.precision_recall_curve` deprecated the keyword argument
|
|||
|
|
`probas_pred` in favor of `y_score`. `probas_pred` will be removed in version 1.7.
|
|||
|
|
:pr:`28092` by :user:`Adam Li <adam2392>`.
|
|||
|
|
|
|||
|
|
- |API| :func:`metrics.brier_score_loss` deprecated the keyword argument `y_prob`
|
|||
|
|
in favor of `y_proba`. `y_prob` will be removed in version 1.7.
|
|||
|
|
:pr:`28092` by :user:`Adam Li <adam2392>`.
|
|||
|
|
|
|||
|
|
- |API| For classifiers and classification metrics, labels encoded as bytes
|
|||
|
|
is deprecated and will raise an error in v1.7.
|
|||
|
|
:pr:`18555` by :user:`Kaushik Amar Das <cozek>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.mixture`
|
|||
|
|
......................
|
|||
|
|
|
|||
|
|
- |Fix| The `converged_` attribute of :class:`mixture.GaussianMixture` and
|
|||
|
|
:class:`mixture.BayesianGaussianMixture` now reflects the convergence status of
|
|||
|
|
the best fit whereas it was previously `True` if any of the fits converged.
|
|||
|
|
:pr:`26837` by :user:`Krsto Proroković <krstopro>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.model_selection`
|
|||
|
|
..............................
|
|||
|
|
|
|||
|
|
- |MajorFeature| :class:`model_selection.TunedThresholdClassifierCV` finds
|
|||
|
|
the decision threshold of a binary classifier that maximizes a
|
|||
|
|
classification metric through cross-validation.
|
|||
|
|
:class:`model_selection.FixedThresholdClassifier` is an alternative when one wants
|
|||
|
|
to use a fixed decision threshold without any tuning scheme.
|
|||
|
|
:pr:`26120` by :user:`Guillaume Lemaitre <glemaitre>`.
|
|||
|
|
|
|||
|
|
- |Enhancement| :term:`CV splitters <CV splitter>` that ignores the group parameter now
|
|||
|
|
raises a warning when groups are passed in to :term:`split`. :pr:`28210` by
|
|||
|
|
`Thomas Fan`_.
|
|||
|
|
|
|||
|
|
- |Enhancement| The HTML diagram representation of
|
|||
|
|
:class:`~model_selection.GridSearchCV`,
|
|||
|
|
:class:`~model_selection.RandomizedSearchCV`,
|
|||
|
|
:class:`~model_selection.HalvingGridSearchCV`, and
|
|||
|
|
:class:`~model_selection.HalvingRandomSearchCV` will show the best estimator when
|
|||
|
|
`refit=True`. :pr:`28722` by :user:`Yao Xiao <Charlie-XIAO>` and `Thomas Fan`_.
|
|||
|
|
|
|||
|
|
- |Fix| the ``cv_results_`` attribute (of :class:`model_selection.GridSearchCV`) now
|
|||
|
|
returns masked arrays of the appropriate NumPy dtype, as opposed to always returning
|
|||
|
|
dtype ``object``. :pr:`28352` by :user:`Marco Gorelli<MarcoGorelli>`.
|
|||
|
|
|
|||
|
|
- |Fix| :func:`model_selection.train_test_split` works with Array API inputs.
|
|||
|
|
Previously indexing was not handled correctly leading to exceptions when using strict
|
|||
|
|
implementations of the Array API like CuPY.
|
|||
|
|
:pr:`28407` by :user:`Tim Head <betatim>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.multioutput`
|
|||
|
|
..........................
|
|||
|
|
|
|||
|
|
- |Enhancement| `chain_method` parameter added to :class:`multioutput.ClassifierChain`.
|
|||
|
|
:pr:`27700` by :user:`Lucy Liu <lucyleeow>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.neighbors`
|
|||
|
|
........................
|
|||
|
|
|
|||
|
|
- |Fix| Fixes :class:`neighbors.NeighborhoodComponentsAnalysis` such that
|
|||
|
|
`get_feature_names_out` returns the correct number of feature names.
|
|||
|
|
:pr:`28306` by :user:`Brendan Lu <brendanlu>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.pipeline`
|
|||
|
|
.......................
|
|||
|
|
|
|||
|
|
- |Feature| :class:`pipeline.FeatureUnion` can now use the
|
|||
|
|
`verbose_feature_names_out` attribute. If `True`, `get_feature_names_out`
|
|||
|
|
will prefix all feature names with the name of the transformer
|
|||
|
|
that generated that feature. If `False`, `get_feature_names_out` will not
|
|||
|
|
prefix any feature names and will error if feature names are not unique.
|
|||
|
|
:pr:`25991` by :user:`Jiawei Zhang <jiawei-zhang-a>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.preprocessing`
|
|||
|
|
............................
|
|||
|
|
|
|||
|
|
- |Enhancement| :class:`preprocessing.QuantileTransformer` and
|
|||
|
|
:func:`preprocessing.quantile_transform` now supports disabling
|
|||
|
|
subsampling explicitly.
|
|||
|
|
:pr:`27636` by :user:`Ralph Urlus <rurlus>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.tree`
|
|||
|
|
...................
|
|||
|
|
|
|||
|
|
- |Enhancement| Plotting trees in matplotlib via :func:`tree.plot_tree` now
|
|||
|
|
show a "True/False" label to indicate the directionality the samples traverse
|
|||
|
|
given the split condition.
|
|||
|
|
:pr:`28552` by :user:`Adam Li <adam2392>`.
|
|||
|
|
|
|||
|
|
:mod:`sklearn.utils`
|
|||
|
|
....................
|
|||
|
|
|
|||
|
|
- |Fix| :func:`~utils._safe_indexing` now works correctly for polars DataFrame when
|
|||
|
|
`axis=0` and supports indexing polars Series.
|
|||
|
|
:pr:`28521` by :user:`Yao Xiao <Charlie-XIAO>`.
|
|||
|
|
|
|||
|
|
- |API| :data:`utils.IS_PYPY` is deprecated and will be removed in version 1.7.
|
|||
|
|
:pr:`28768` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
|
|||
|
|
|
|||
|
|
- |API| :func:`utils.tosequence` is deprecated and will be removed in version 1.7.
|
|||
|
|
:pr:`28763` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
|
|||
|
|
|
|||
|
|
- |API| :class:`utils.parallel_backend` and :func:`utils.register_parallel_backend` are
|
|||
|
|
deprecated and will be removed in version 1.7. Use `joblib.parallel_backend` and
|
|||
|
|
`joblib.register_parallel_backend` instead.
|
|||
|
|
:pr:`28847` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
|
|||
|
|
|
|||
|
|
- |API| Raise informative warning message in :func:`~utils.multiclass.type_of_target`
|
|||
|
|
when represented as bytes. For classifiers and classification metrics, labels encoded
|
|||
|
|
as bytes is deprecated and will raise an error in v1.7.
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:pr:`18555` by :user:`Kaushik Amar Das <cozek>`.
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- |API| :func:`utils.estimator_checks.check_estimator_sparse_data` was split into two
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functions: :func:`utils.estimator_checks.check_estimator_sparse_matrix` and
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:func:`utils.estimator_checks.check_estimator_sparse_array`.
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:pr:`27576` by :user:`Stefanie Senger <StefanieSenger>`.
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.. rubric:: Code and documentation contributors
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Thanks to everyone who has contributed to the maintenance and improvement of
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the project since version 1.4, including:
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101AlexMartin, Abdulaziz Aloqeely, Adam J. Stewart, Adam Li, Adarsh Wase, Adrin
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Jalali, Advik Sinha, Akash Srivastava, Akihiro Kuno, Alan Guedes, Alexis
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IMBERT, Ana Paula Gomes, Anderson Nelson, Andrei Dzis, Arnaud Capitaine, Arturo
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Amor, Aswathavicky, Bharat Raghunathan, Brendan Lu, Bruno, Cemlyn, Christian
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Lorentzen, Christian Veenhuis, Cindy Liang, Claudio Salvatore Arcidiacono,
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Connor Boyle, Conrad Stevens, crispinlogan, davidleon123, DerWeh, Dipan Banik,
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Duarte São José, DUONG, Eddie Bergman, Edoardo Abati, Egehan Gunduz, Emad
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Izadifar, Erich Schubert, Filip Karlo Došilović, Franck Charras, Gael
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Varoquaux, Gönül Aycı, Guillaume Lemaitre, Gyeongjae Choi, Harmanan Kohli,
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Hong Xiang Yue, Ian Faust, itsaphel, Ivan Wiryadi, Jack Bowyer, Javier Marin
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Tur, Jérémie du Boisberranger, Jérôme Dockès, Jiawei Zhang, Joel Nothman,
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Johanna Bayer, John Cant, John Hopfensperger, jpcars, jpienaar-tuks, Julian
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Libiseller-Egger, Julien Jerphanion, KanchiMoe, Kaushik Amar Das, keyber,
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Koustav Ghosh, kraktus, Krsto Proroković, ldwy4, LeoGrin, lihaitao, Linus
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Sommer, Loic Esteve, Lucy Liu, Lukas Geiger, manasimj, Manuel Labbé, Manuel
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Morales, Marco Edward Gorelli, Maren Westermann, Marija Vlajic, Mark Elliot,
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Mateusz Sokół, Mavs, Michael Higgins, Michael Mayer, miguelcsilva, Miki
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Watanabe, Mohammed Hamdy, myenugula, Nathan Goldbaum, Naziya Mahimkar, Neto,
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Olivier Grisel, Omar Salman, Patrick Wang, Pierre de Fréminville, Priyash
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Shah, Puneeth K, Rahil Parikh, raisadz, Raj Pulapakura, Ralf Gommers, Ralph
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Urlus, Randolf Scholz, Reshama Shaikh, Richard Barnes, Rodrigo Romero, Saad
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Mahmood, Salim Dohri, Sandip Dutta, SarahRemus, scikit-learn-bot, Shaharyar
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Choudhry, Shubham, sperret6, Stefanie Senger, Suha Siddiqui, Thanh Lam DANG,
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thebabush, Thomas J. Fan, Thomas Lazarus, Thomas Li, Tialo, Tim Head, Tuhin
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Sharma, VarunChaduvula, Vineet Joshi, virchan, Waël Boukhobza, Weyb, Will
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Dean, Xavier Beltran, Xiao Yuan, Xuefeng Xu, Yao Xiao
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