.. include:: _contributors.rst

.. currentmodule:: sklearn

.. _release_notes_1_2:

===========
Version 1.2
===========

For a short description of the main highlights of the release, please refer to
:ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_2_0.py`.

.. include:: changelog_legend.inc

.. _changes_1_2_2:

Version 1.2.2
=============

**March 2023**

Changelog
---------

:mod:`sklearn.base`
...................

- |Fix| When `set_output(transform="pandas")`, :class:`base.TransformerMixin` maintains
  the index if the :term:`transform` output is already a DataFrame. :pr:`25747` by
  `Thomas Fan`_.

:mod:`sklearn.calibration`
..........................

- |Fix| A deprecation warning is raised when using the `base_estimator__` prefix to
  set parameters of the estimator used in :class:`calibration.CalibratedClassifierCV`.
  :pr:`25477` by :user:`Tim Head <betatim>`.

:mod:`sklearn.cluster`
......................

- |Fix| Fixed a bug in :class:`cluster.BisectingKMeans`, preventing `fit` to randomly
  fail due to a permutation of the labels when running multiple inits.
  :pr:`25563` by :user:`Jérémie du Boisberranger <jeremiedbb>`.

:mod:`sklearn.compose`
......................

- |Fix| Fixes a bug in :class:`compose.ColumnTransformer` which now supports
  empty selection of columns when `set_output(transform="pandas")`.
  :pr:`25570` by `Thomas Fan`_.

:mod:`sklearn.ensemble`
.......................

- |Fix| A deprecation warning is raised when using the `base_estimator__` prefix
  to set parameters of the estimator used in :class:`ensemble.AdaBoostClassifier`,
  :class:`ensemble.AdaBoostRegressor`, :class:`ensemble.BaggingClassifier`,
  and :class:`ensemble.BaggingRegressor`.
  :pr:`25477` by :user:`Tim Head <betatim>`.

:mod:`sklearn.feature_selection`
................................

- |Fix| Fixed a regression where a negative `tol` would not be accepted any more by
  :class:`feature_selection.SequentialFeatureSelector`.
  :pr:`25664` by :user:`Jérémie du Boisberranger <jeremiedbb>`.

:mod:`sklearn.inspection`
.........................

- |Fix| Raise a more informative error message in :func:`inspection.partial_dependence`
  when dealing with mixed data type categories that cannot be sorted by
  :func:`numpy.unique`. This problem usually happen when categories are `str` and
  missing values are present using `np.nan`.
  :pr:`25774` by :user:`Guillaume Lemaitre <glemaitre>`.

:mod:`sklearn.isotonic`
.......................

- |Fix| Fixes a bug in :class:`isotonic.IsotonicRegression` where
  :meth:`isotonic.IsotonicRegression.predict` would return a pandas DataFrame
  when the global configuration sets `transform_output="pandas"`.
  :pr:`25500` by :user:`Guillaume Lemaitre <glemaitre>`.

:mod:`sklearn.preprocessing`
............................

- |Fix| `preprocessing.OneHotEncoder.drop_idx_` now properly
  references the dropped category in the `categories_` attribute
  when there are infrequent categories. :pr:`25589` by `Thomas Fan`_.

- |Fix| :class:`preprocessing.OrdinalEncoder` now correctly supports
  `encoded_missing_value` or `unknown_value` set to a categories' cardinality
  when there is missing values in the training data. :pr:`25704` by `Thomas Fan`_.

:mod:`sklearn.tree`
...................

- |Fix| Fixed a regression in :class:`tree.DecisionTreeClassifier`,
  :class:`tree.DecisionTreeRegressor`, :class:`tree.ExtraTreeClassifier` and
  :class:`tree.ExtraTreeRegressor` where an error was no longer raised in version
  1.2 when `min_sample_split=1`.
  :pr:`25744` by :user:`Jérémie du Boisberranger <jeremiedbb>`.

:mod:`sklearn.utils`
....................

- |Fix| Fixes a bug in :func:`utils.check_array` which now correctly performs
  non-finite validation with the Array API specification. :pr:`25619` by
  `Thomas Fan`_.

- |Fix| :func:`utils.multiclass.type_of_target` can identify pandas
  nullable data types as classification targets. :pr:`25638` by `Thomas Fan`_.

.. _changes_1_2_1:

Version 1.2.1
=============

**January 2023**

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 fitted components in
  :class:`decomposition.MiniBatchDictionaryLearning` might differ. The online
  updates of the sufficient statistics now properly take the sizes of the
  batches into account.
  :pr:`25354` by :user:`Jérémie du Boisberranger <jeremiedbb>`.

- |Fix| The `categories_` attribute of :class:`preprocessing.OneHotEncoder` now
  always contains an array of `object`s when using predefined categories that
  are strings. Predefined categories encoded as bytes will no longer work
  with `X` encoded as strings. :pr:`25174` by :user:`Tim Head <betatim>`.

Changes impacting all modules
-----------------------------

- |Fix| Support `pandas.Int64` dtyped `y` for classifiers and regressors.
  :pr:`25089` by :user:`Tim Head <betatim>`.

- |Fix| Remove spurious warnings for estimators internally using neighbors search methods.
  :pr:`25129` by :user:`Julien Jerphanion <jjerphan>`.

- |Fix| Fix a bug where the current configuration was ignored in estimators using
  `n_jobs > 1`. This bug was triggered for tasks dispatched by the auxiliary
  thread of `joblib` as :func:`sklearn.get_config` used to access an empty thread
  local configuration instead of the configuration visible from the thread where
  `joblib.Parallel` was first called.
  :pr:`25363` by :user:`Guillaume Lemaitre <glemaitre>`.

Changelog
---------

:mod:`sklearn.base`
...................

- |Fix| Fix a regression in `BaseEstimator.__getstate__` that would prevent
  certain estimators to be pickled when using Python 3.11. :pr:`25188` by
  :user:`Benjamin Bossan <BenjaminBossan>`.

- |Fix| Inheriting from :class:`base.TransformerMixin` will only wrap the `transform`
  method if the class defines `transform` itself. :pr:`25295` by `Thomas Fan`_.

:mod:`sklearn.datasets`
.......................

- |Fix| Fixes an inconsistency in :func:`datasets.fetch_openml` between liac-arff
  and pandas parser when a leading space is introduced after the delimiter.
  The ARFF specs requires to ignore the leading space.
  :pr:`25312` by :user:`Guillaume Lemaitre <glemaitre>`.

- |Fix| Fixes a bug in :func:`datasets.fetch_openml` when using `parser="pandas"`
  where single quote and backslash escape characters were not properly handled.
  :pr:`25511` by :user:`Guillaume Lemaitre <glemaitre>`.

:mod:`sklearn.decomposition`
............................

- |Fix| Fixed a bug in :class:`decomposition.MiniBatchDictionaryLearning` where the
  online updates of the sufficient statistics where not correct when calling
  `partial_fit` on batches of different sizes.
  :pr:`25354` by :user:`Jérémie du Boisberranger <jeremiedbb>`.

- |Fix| :class:`decomposition.DictionaryLearning` better supports readonly NumPy
  arrays. In particular, it better supports large datasets which are memory-mapped
  when it is used with coordinate descent algorithms (i.e. when `fit_algorithm='cd'`).
  :pr:`25172` by :user:`Julien Jerphanion <jjerphan>`.

:mod:`sklearn.ensemble`
.......................

- |Fix| :class:`ensemble.RandomForestClassifier`,
  :class:`ensemble.RandomForestRegressor` :class:`ensemble.ExtraTreesClassifier`
  and :class:`ensemble.ExtraTreesRegressor` now support sparse readonly datasets.
  :pr:`25341` by :user:`Julien Jerphanion <jjerphan>`

:mod:`sklearn.feature_extraction`
.................................

- |Fix| :class:`feature_extraction.FeatureHasher` raises an informative error
  when the input is a list of strings. :pr:`25094` by `Thomas Fan`_.

:mod:`sklearn.linear_model`
...........................

- |Fix| Fix a regression in :class:`linear_model.SGDClassifier` and
  :class:`linear_model.SGDRegressor` that makes them unusable with the
  `verbose` parameter set to a value greater than 0.
  :pr:`25250` by :user:`Jérémie Du Boisberranger <jeremiedbb>`.

:mod:`sklearn.manifold`
.......................

- |Fix| :class:`manifold.TSNE` now works correctly when output type is
  set to pandas :pr:`25370` by :user:`Tim Head <betatim>`.

:mod:`sklearn.model_selection`
..............................

- |Fix| :func:`model_selection.cross_validate` with multimetric scoring in
  case of some failing scorers the non-failing scorers now returns proper
  scores instead of `error_score` values.
  :pr:`23101` by :user:`András Simon <simonandras>` and `Thomas Fan`_.

:mod:`sklearn.neural_network`
.............................

- |Fix| :class:`neural_network.MLPClassifier` and :class:`neural_network.MLPRegressor`
  no longer raise warnings when fitting data with feature names.
  :pr:`24873` by :user:`Tim Head <betatim>`.

- |Fix| Improves error message in :class:`neural_network.MLPClassifier` and
  :class:`neural_network.MLPRegressor`, when `early_stopping=True` and
  `partial_fit` is called. :pr:`25694` by `Thomas Fan`_.

:mod:`sklearn.preprocessing`
............................

- |Fix| :meth:`preprocessing.FunctionTransformer.inverse_transform` correctly
  supports DataFrames that are all numerical when `check_inverse=True`.
  :pr:`25274` by `Thomas Fan`_.

- |Fix| :meth:`preprocessing.SplineTransformer.get_feature_names_out` correctly
  returns feature names when `extrapolations="periodic"`. :pr:`25296` by
  `Thomas Fan`_.

:mod:`sklearn.tree`
...................

- |Fix| :class:`tree.DecisionTreeClassifier`, :class:`tree.DecisionTreeRegressor`
  :class:`tree.ExtraTreeClassifier` and :class:`tree.ExtraTreeRegressor`
  now support sparse readonly datasets.
  :pr:`25341` by :user:`Julien Jerphanion <jjerphan>`

:mod:`sklearn.utils`
....................

- |Fix| Restore :func:`utils.check_array`'s behaviour for pandas Series of type
  boolean. The type is maintained, instead of converting to `float64.`
  :pr:`25147` by :user:`Tim Head <betatim>`.

- |API| `utils.fixes.delayed` is deprecated in 1.2.1 and will be removed
  in 1.5. Instead, import :func:`utils.parallel.delayed` and use it in
  conjunction with the newly introduced :func:`utils.parallel.Parallel`
  to ensure proper propagation of the scikit-learn configuration to
  the workers.
  :pr:`25363` by :user:`Guillaume Lemaitre <glemaitre>`.

.. _changes_1_2:

Version 1.2.0
=============

**December 2022**

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.

- |Enhancement| The default `eigen_tol` for :class:`cluster.SpectralClustering`,
  :class:`manifold.SpectralEmbedding`, :func:`cluster.spectral_clustering`,
  and :func:`manifold.spectral_embedding` is now `None` when using the `'amg'`
  or `'lobpcg'` solvers. This change improves numerical stability of the
  solver, but may result in a different model.

- |Enhancement| :class:`linear_model.GammaRegressor`,
  :class:`linear_model.PoissonRegressor` and :class:`linear_model.TweedieRegressor`
  can reach higher precision with the lbfgs solver, in particular when `tol` is set
  to a tiny value. Moreover, `verbose` is now properly propagated to L-BFGS-B.
  :pr:`23619` by :user:`Christian Lorentzen <lorentzenchr>`.

- |Enhancement| The default value for `eps` :func:`metrics.log_loss` has changed
  from `1e-15` to `"auto"`. `"auto"` sets `eps` to `np.finfo(y_pred.dtype).eps`.
  :pr:`24354` by :user:`Safiuddin Khaja <Safikh>` and :user:`gsiisg <gsiisg>`.

- |Fix| Make sign of `components_` deterministic in :class:`decomposition.SparsePCA`.
  :pr:`23935` by :user:`Guillaume Lemaitre <glemaitre>`.

- |Fix| The `components_` signs in :class:`decomposition.FastICA` might differ.
  It is now consistent and deterministic with all SVD solvers.
  :pr:`22527` by :user:`Meekail Zain <micky774>` and `Thomas Fan`_.

- |Fix| The condition for early stopping has now been changed in
  `linear_model._sgd_fast._plain_sgd` which is used by
  :class:`linear_model.SGDRegressor` and :class:`linear_model.SGDClassifier`. The old
  condition did not disambiguate between
  training and validation set and had an effect of overscaling the error tolerance.
  This has been fixed in :pr:`23798` by :user:`Harsh Agrawal <Harsh14901>`.

- |Fix| For :class:`model_selection.GridSearchCV` and
  :class:`model_selection.RandomizedSearchCV` ranks corresponding to nan
  scores will all be set to the maximum possible rank.
  :pr:`24543` by :user:`Guillaume Lemaitre <glemaitre>`.

- |API| The default value of `tol` was changed from `1e-3` to `1e-4` for
  :func:`linear_model.ridge_regression`, :class:`linear_model.Ridge` and
  :class:`linear_model.RidgeClassifier`.
  :pr:`24465` by :user:`Christian Lorentzen <lorentzenchr>`.

Changes impacting all modules
-----------------------------

- |MajorFeature| The `set_output` API has been adopted by all transformers.
  Meta-estimators that contain transformers such as :class:`pipeline.Pipeline`
  or :class:`compose.ColumnTransformer` also define a `set_output`.
  For details, see
  `SLEP018 <https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html>`__.
  :pr:`23734` and :pr:`24699` by `Thomas Fan`_.

- |Efficiency| Low-level routines for reductions on pairwise distances
  for dense float32 datasets have been refactored. The following functions
  and estimators now benefit from improved performances in terms of hardware
  scalability and speed-ups:

  - :func:`sklearn.metrics.pairwise_distances_argmin`
  - :func:`sklearn.metrics.pairwise_distances_argmin_min`
  - :class:`sklearn.cluster.AffinityPropagation`
  - :class:`sklearn.cluster.Birch`
  - :class:`sklearn.cluster.MeanShift`
  - :class:`sklearn.cluster.OPTICS`
  - :class:`sklearn.cluster.SpectralClustering`
  - :func:`sklearn.feature_selection.mutual_info_regression`
  - :class:`sklearn.neighbors.KNeighborsClassifier`
  - :class:`sklearn.neighbors.KNeighborsRegressor`
  - :class:`sklearn.neighbors.RadiusNeighborsClassifier`
  - :class:`sklearn.neighbors.RadiusNeighborsRegressor`
  - :class:`sklearn.neighbors.LocalOutlierFactor`
  - :class:`sklearn.neighbors.NearestNeighbors`
  - :class:`sklearn.manifold.Isomap`
  - :class:`sklearn.manifold.LocallyLinearEmbedding`
  - :class:`sklearn.manifold.TSNE`
  - :func:`sklearn.manifold.trustworthiness`
  - :class:`sklearn.semi_supervised.LabelPropagation`
  - :class:`sklearn.semi_supervised.LabelSpreading`

  For instance :meth:`sklearn.neighbors.NearestNeighbors.kneighbors` and
  :meth:`sklearn.neighbors.NearestNeighbors.radius_neighbors`
  can respectively be up to ×20 and ×5 faster than previously on a laptop.

  Moreover, implementations of those two algorithms are now suitable
  for machine with many cores, making them usable for datasets consisting
  of millions of samples.

  :pr:`23865` by :user:`Julien Jerphanion <jjerphan>`.

- |Enhancement| Finiteness checks (detection of NaN and infinite values) in all
  estimators are now significantly more efficient for float32 data by leveraging
  NumPy's SIMD optimized primitives.
  :pr:`23446` by :user:`Meekail Zain <micky774>`

- |Enhancement| Finiteness checks (detection of NaN and infinite values) in all
  estimators are now faster by utilizing a more efficient stop-on-first
  second-pass algorithm.
  :pr:`23197` by :user:`Meekail Zain <micky774>`

- |Enhancement| Support for combinations of dense and sparse datasets pairs
  for all distance metrics and for float32 and float64 datasets has been added
  or has seen its performance improved for the following estimators:

  - :func:`sklearn.metrics.pairwise_distances_argmin`
  - :func:`sklearn.metrics.pairwise_distances_argmin_min`
  - :class:`sklearn.cluster.AffinityPropagation`
  - :class:`sklearn.cluster.Birch`
  - :class:`sklearn.cluster.SpectralClustering`
  - :class:`sklearn.neighbors.KNeighborsClassifier`
  - :class:`sklearn.neighbors.KNeighborsRegressor`
  - :class:`sklearn.neighbors.RadiusNeighborsClassifier`
  - :class:`sklearn.neighbors.RadiusNeighborsRegressor`
  - :class:`sklearn.neighbors.LocalOutlierFactor`
  - :class:`sklearn.neighbors.NearestNeighbors`
  - :class:`sklearn.manifold.Isomap`
  - :class:`sklearn.manifold.TSNE`
  - :func:`sklearn.manifold.trustworthiness`

  :pr:`23604` and :pr:`23585` by :user:`Julien Jerphanion <jjerphan>`,
  :user:`Olivier Grisel <ogrisel>`, and `Thomas Fan`_,
  :pr:`24556` by :user:`Vincent Maladière <Vincent-Maladiere>`.

- |Fix| Systematically check the sha256 digest of dataset tarballs used in code
  examples in the documentation.
  :pr:`24617` by :user:`Olivier Grisel <ogrisel>` and `Thomas Fan`_. Thanks to
  `Sim4n6 <https://huntr.dev/users/sim4n6>`_ for the report.

Changelog
---------

..
    Entries should be grouped by module (in alphabetic order) and prefixed with
    one of the labels: |MajorFeature|, |Feature|, |Efficiency|, |Enhancement|,
    |Fix| or |API| (see whats_new.rst for descriptions).
    Entries should be ordered by those labels (e.g. |Fix| after |Efficiency|).
    Changes not specific to a module should be listed under *Multiple Modules*
    or *Miscellaneous*.
    Entries should end with:
    :pr:`123456` by :user:`Joe Bloggs <joeongithub>`.
    where 123456 is the *pull request* number, not the issue number.

:mod:`sklearn.base`
...................

- |Enhancement| Introduces :class:`base.ClassNamePrefixFeaturesOutMixin` and
  :class:`base.ClassNamePrefixFeaturesOutMixin` mixins that defines
  :term:`get_feature_names_out` for common transformer uses cases.
  :pr:`24688` by `Thomas Fan`_.

:mod:`sklearn.calibration`
..........................

- |API| Rename `base_estimator` to `estimator` in
  :class:`calibration.CalibratedClassifierCV` to improve readability and consistency.
  The parameter `base_estimator` is deprecated and will be removed in 1.4.
  :pr:`22054` by :user:`Kevin Roice <kevroi>`.

:mod:`sklearn.cluster`
......................

- |Efficiency| :class:`cluster.KMeans` with `algorithm="lloyd"` is now faster
  and uses less memory. :pr:`24264` by
  :user:`Vincent Maladiere <Vincent-Maladiere>`.

- |Enhancement| The `predict` and `fit_predict` methods of :class:`cluster.OPTICS` now
  accept sparse data type for input data. :pr:`14736` by :user:`Hunt Zhan <huntzhan>`,
  :pr:`20802` by :user:`Brandon Pokorny <Clickedbigfoot>`,
  and :pr:`22965` by :user:`Meekail Zain <micky774>`.

- |Enhancement| :class:`cluster.Birch` now preserves dtype for `numpy.float32`
  inputs. :pr:`22968` by `Meekail Zain <micky774>`.

- |Enhancement| :class:`cluster.KMeans` and :class:`cluster.MiniBatchKMeans`
  now accept a new `'auto'` option for `n_init` which changes the number of
  random initializations to one when using `init='k-means++'` for efficiency.
  This begins deprecation for the default values of `n_init` in the two classes
  and both will have their defaults changed to `n_init='auto'` in 1.4.
  :pr:`23038` by :user:`Meekail Zain <micky774>`.

- |Enhancement| :class:`cluster.SpectralClustering` and
  :func:`cluster.spectral_clustering` now propagates the `eigen_tol` parameter
  to all choices of `eigen_solver`. Includes a new option `eigen_tol="auto"`
  and begins deprecation to change the default from `eigen_tol=0` to
  `eigen_tol="auto"` in version 1.3.
  :pr:`23210` by :user:`Meekail Zain <micky774>`.

- |Fix| :class:`cluster.KMeans` now supports readonly attributes when predicting.
  :pr:`24258` by `Thomas Fan`_

- |API| The `affinity` attribute is now deprecated for
  :class:`cluster.AgglomerativeClustering` and will be renamed to `metric` in v1.4.
  :pr:`23470` by :user:`Meekail Zain <micky774>`.

:mod:`sklearn.datasets`
.......................

- |Enhancement| Introduce the new parameter `parser` in
  :func:`datasets.fetch_openml`. `parser="pandas"` allows to use the very CPU
  and memory efficient `pandas.read_csv` parser to load dense ARFF
  formatted dataset files. It is possible to pass `parser="liac-arff"`
  to use the old LIAC parser.
  When `parser="auto"`, dense datasets are loaded with "pandas" and sparse
  datasets are loaded with "liac-arff".
  Currently, `parser="liac-arff"` by default and will change to `parser="auto"`
  in version 1.4
  :pr:`21938` by :user:`Guillaume Lemaitre <glemaitre>`.

- |Enhancement| :func:`datasets.dump_svmlight_file` is now accelerated with a
  Cython implementation, providing 2-4x speedups.
  :pr:`23127` by :user:`Meekail Zain <micky774>`

- |Enhancement| Path-like objects, such as those created with pathlib are now
  allowed as paths in :func:`datasets.load_svmlight_file` and
  :func:`datasets.load_svmlight_files`.
  :pr:`19075` by :user:`Carlos Ramos Carreño <vnmabus>`.

- |Fix| Make sure that :func:`datasets.fetch_lfw_people` and
  :func:`datasets.fetch_lfw_pairs` internally crops images based on the
  `slice_` parameter.
  :pr:`24951` by :user:`Guillaume Lemaitre <glemaitre>`.

:mod:`sklearn.decomposition`
............................

- |Efficiency| :func:`decomposition.FastICA.fit` has been optimised w.r.t
  its memory footprint and runtime.
  :pr:`22268` by :user:`MohamedBsh <Bsh>`.

- |Enhancement| :class:`decomposition.SparsePCA` and
  :class:`decomposition.MiniBatchSparsePCA` now implements an `inverse_transform`
  function.
  :pr:`23905` by :user:`Guillaume Lemaitre <glemaitre>`.

- |Enhancement| :class:`decomposition.FastICA` now allows the user to select
  how whitening is performed through the new `whiten_solver` parameter, which
  supports `svd` and `eigh`. `whiten_solver` defaults to `svd` although `eigh`
  may be faster and more memory efficient in cases where
  `num_features > num_samples`.
  :pr:`11860` by :user:`Pierre Ablin <pierreablin>`,
  :pr:`22527` by :user:`Meekail Zain <micky774>` and `Thomas Fan`_.

- |Enhancement| :class:`decomposition.LatentDirichletAllocation` now preserves dtype
  for `numpy.float32` input. :pr:`24528` by :user:`Takeshi Oura <takoika>` and
  :user:`Jérémie du Boisberranger <jeremiedbb>`.

- |Fix| Make sign of `components_` deterministic in :class:`decomposition.SparsePCA`.
  :pr:`23935` by :user:`Guillaume Lemaitre <glemaitre>`.

- |API| The `n_iter` parameter of :class:`decomposition.MiniBatchSparsePCA` is
  deprecated and replaced by the parameters `max_iter`, `tol`, and
  `max_no_improvement` to be consistent with
  :class:`decomposition.MiniBatchDictionaryLearning`. `n_iter` will be removed
  in version 1.3. :pr:`23726` by :user:`Guillaume Lemaitre <glemaitre>`.

- |API| The `n_features_` attribute of
  :class:`decomposition.PCA` is deprecated in favor of
  `n_features_in_` and will be removed in 1.4. :pr:`24421` by
  :user:`Kshitij Mathur <Kshitij68>`.

:mod:`sklearn.discriminant_analysis`
....................................

- |MajorFeature| :class:`discriminant_analysis.LinearDiscriminantAnalysis` now
  supports the `Array API <https://data-apis.org/array-api/latest/>`_ for
  `solver="svd"`. Array API support is considered experimental and might evolve
  without being subjected to our usual rolling deprecation cycle policy. See
  :ref:`array_api` for more details. :pr:`22554` by `Thomas Fan`_.

- |Fix| Validate parameters only in `fit` and not in `__init__`
  for :class:`discriminant_analysis.QuadraticDiscriminantAnalysis`.
  :pr:`24218` by :user:`Stefanie Molin <stefmolin>`.

:mod:`sklearn.ensemble`
.......................

- |MajorFeature| :class:`ensemble.HistGradientBoostingClassifier` and
  :class:`ensemble.HistGradientBoostingRegressor` now support
  interaction constraints via the argument `interaction_cst` of their
  constructors.
  :pr:`21020` by :user:`Christian Lorentzen <lorentzenchr>`.
  Using interaction constraints also makes fitting faster.
  :pr:`24856` by :user:`Christian Lorentzen <lorentzenchr>`.

- |Feature| Adds `class_weight` to :class:`ensemble.HistGradientBoostingClassifier`.
  :pr:`22014` by `Thomas Fan`_.

- |Efficiency| Improve runtime performance of :class:`ensemble.IsolationForest`
  by avoiding data copies. :pr:`23252` by :user:`Zhehao Liu <MaxwellLZH>`.

- |Enhancement| :class:`ensemble.StackingClassifier` now accepts any kind of
  base estimator.
  :pr:`24538` by :user:`Guillem G Subies <GuillemGSubies>`.

- |Enhancement| Make it possible to pass the `categorical_features` parameter
  of :class:`ensemble.HistGradientBoostingClassifier` and
  :class:`ensemble.HistGradientBoostingRegressor` as feature names.
  :pr:`24889` by :user:`Olivier Grisel <ogrisel>`.

- |Enhancement| :class:`ensemble.StackingClassifier` now supports
  multilabel-indicator target
  :pr:`24146` by :user:`Nicolas Peretti <nicoperetti>`,
  :user:`Nestor Navarro <nestornav>`, :user:`Nati Tomattis <natitomattis>`,
  and :user:`Vincent Maladiere <Vincent-Maladiere>`.

- |Enhancement| :class:`ensemble.HistGradientBoostingClassifier` and
  :class:`ensemble.HistGradientBoostingClassifier` now accept their
  `monotonic_cst` parameter to be passed as a dictionary in addition
  to the previously supported array-like format.
  Such dictionary have feature names as keys and one of `-1`, `0`, `1`
  as value to specify monotonicity constraints for each feature.
  :pr:`24855` by :user:`Olivier Grisel <ogrisel>`.

- |Enhancement| Interaction constraints for
  :class:`ensemble.HistGradientBoostingClassifier`
  and :class:`ensemble.HistGradientBoostingRegressor` can now be specified
  as strings for two common cases: "no_interactions" and "pairwise" interactions.
  :pr:`24849` by :user:`Tim Head <betatim>`.

- |Fix| Fixed the issue where :class:`ensemble.AdaBoostClassifier` outputs
  NaN in feature importance when fitted with very small sample weight.
  :pr:`20415` by :user:`Zhehao Liu <MaxwellLZH>`.

- |Fix| :class:`ensemble.HistGradientBoostingClassifier` and
  :class:`ensemble.HistGradientBoostingRegressor` no longer error when predicting
  on categories encoded as negative values and instead consider them a member
  of the "missing category". :pr:`24283` by `Thomas Fan`_.

- |Fix| :class:`ensemble.HistGradientBoostingClassifier` and
  :class:`ensemble.HistGradientBoostingRegressor`, with `verbose>=1`, print detailed
  timing information on computing histograms and finding best splits. The time spent in
  the root node was previously missing and is now included in the printed information.
  :pr:`24894` by :user:`Christian Lorentzen <lorentzenchr>`.

- |API| Rename the constructor parameter `base_estimator` to `estimator` in
  the following classes:
  :class:`ensemble.BaggingClassifier`,
  :class:`ensemble.BaggingRegressor`,
  :class:`ensemble.AdaBoostClassifier`,
  :class:`ensemble.AdaBoostRegressor`.
  `base_estimator` is deprecated in 1.2 and will be removed in 1.4.
  :pr:`23819` by :user:`Adrian Trujillo <trujillo9616>` and
  :user:`Edoardo Abati <EdAbati>`.

- |API| Rename the fitted attribute `base_estimator_` to `estimator_` in
  the following classes:
  :class:`ensemble.BaggingClassifier`,
  :class:`ensemble.BaggingRegressor`,
  :class:`ensemble.AdaBoostClassifier`,
  :class:`ensemble.AdaBoostRegressor`,
  :class:`ensemble.RandomForestClassifier`,
  :class:`ensemble.RandomForestRegressor`,
  :class:`ensemble.ExtraTreesClassifier`,
  :class:`ensemble.ExtraTreesRegressor`,
  :class:`ensemble.RandomTreesEmbedding`,
  :class:`ensemble.IsolationForest`.
  `base_estimator_` is deprecated in 1.2 and will be removed in 1.4.
  :pr:`23819` by :user:`Adrian Trujillo <trujillo9616>` and
  :user:`Edoardo Abati <EdAbati>`.

:mod:`sklearn.feature_selection`
................................

- |Fix| Fix a bug in :func:`feature_selection.mutual_info_regression` and
  :func:`feature_selection.mutual_info_classif`, where the continuous features
  in `X` should be scaled to a unit variance independently if the target `y` is
  continuous or discrete.
  :pr:`24747` by :user:`Guillaume Lemaitre <glemaitre>`

:mod:`sklearn.gaussian_process`
...............................

- |Fix| Fix :class:`gaussian_process.kernels.Matern` gradient computation with
  `nu=0.5` for PyPy (and possibly other non CPython interpreters). :pr:`24245`
  by :user:`Loïc Estève <lesteve>`.

- |Fix| The `fit` method of :class:`gaussian_process.GaussianProcessRegressor`
  will not modify the input X in case a custom kernel is used, with a `diag`
  method that returns part of the input X. :pr:`24405`
  by :user:`Omar Salman <OmarManzoor>`.

:mod:`sklearn.impute`
.....................

- |Enhancement| Added `keep_empty_features` parameter to
  :class:`impute.SimpleImputer`, :class:`impute.KNNImputer` and
  :class:`impute.IterativeImputer`, preventing removal of features
  containing only missing values when transforming.
  :pr:`16695` by :user:`Vitor Santa Rosa <vitorsrg>`.

:mod:`sklearn.inspection`
.........................

- |MajorFeature| Extended :func:`inspection.partial_dependence` and
  :class:`inspection.PartialDependenceDisplay` to handle categorical features.
  :pr:`18298` by :user:`Madhura Jayaratne <madhuracj>` and
  :user:`Guillaume Lemaitre <glemaitre>`.

- |Fix| :class:`inspection.DecisionBoundaryDisplay` now raises error if input
  data is not 2-dimensional.
  :pr:`25077` by :user:`Arturo Amor <ArturoAmorQ>`.

:mod:`sklearn.kernel_approximation`
...................................

- |Enhancement| :class:`kernel_approximation.RBFSampler` now preserves
  dtype for `numpy.float32` inputs. :pr:`24317` by `Tim Head <betatim>`.

- |Enhancement| :class:`kernel_approximation.SkewedChi2Sampler` now preserves
  dtype for `numpy.float32` inputs. :pr:`24350` by :user:`Rahil Parikh <rprkh>`.

- |Enhancement| :class:`kernel_approximation.RBFSampler` now accepts
  `'scale'` option for parameter `gamma`.
  :pr:`24755` by :user:`Gleb Levitski <GLevV>`.

:mod:`sklearn.linear_model`
...........................

- |Enhancement| :class:`linear_model.LogisticRegression`,
  :class:`linear_model.LogisticRegressionCV`, :class:`linear_model.GammaRegressor`,
  :class:`linear_model.PoissonRegressor` and :class:`linear_model.TweedieRegressor` got
  a new solver `solver="newton-cholesky"`. This is a 2nd order (Newton) optimisation
  routine that uses a Cholesky decomposition of the hessian matrix.
  When `n_samples >> n_features`, the `"newton-cholesky"` solver has been observed to
  converge both faster and to a higher precision solution than the `"lbfgs"` solver on
  problems with one-hot encoded categorical variables with some rare categorical
  levels.
  :pr:`24637` and :pr:`24767` by :user:`Christian Lorentzen <lorentzenchr>`.

- |Enhancement| :class:`linear_model.GammaRegressor`,
  :class:`linear_model.PoissonRegressor` and :class:`linear_model.TweedieRegressor`
  can reach higher precision with the lbfgs solver, in particular when `tol` is set
  to a tiny value. Moreover, `verbose` is now properly propagated to L-BFGS-B.
  :pr:`23619` by :user:`Christian Lorentzen <lorentzenchr>`.

- |Fix| :class:`linear_model.SGDClassifier` and :class:`linear_model.SGDRegressor` will
  raise an error when all the validation samples have zero sample weight.
  :pr:`23275` by `Zhehao Liu <MaxwellLZH>`.

- |Fix| :class:`linear_model.SGDOneClassSVM` no longer performs parameter
  validation in the constructor. All validation is now handled in `fit()` and
  `partial_fit()`.
  :pr:`24433` by :user:`Yogendrasingh <iofall>`, :user:`Arisa Y. <arisayosh>`
  and :user:`Tim Head <betatim>`.

- |Fix| Fix average loss calculation when early stopping is enabled in
  :class:`linear_model.SGDRegressor` and :class:`linear_model.SGDClassifier`.
  Also updated the condition for early stopping accordingly.
  :pr:`23798` by :user:`Harsh Agrawal <Harsh14901>`.

- |API| The default value for the `solver` parameter in
  :class:`linear_model.QuantileRegressor` will change from `"interior-point"`
  to `"highs"` in version 1.4.
  :pr:`23637` by :user:`Guillaume Lemaitre <glemaitre>`.

- |API| String option `"none"` is deprecated for `penalty` argument
  in :class:`linear_model.LogisticRegression`, and will be removed in version 1.4.
  Use `None` instead. :pr:`23877` by :user:`Zhehao Liu <MaxwellLZH>`.

- |API| The default value of `tol` was changed from `1e-3` to `1e-4` for
  :func:`linear_model.ridge_regression`, :class:`linear_model.Ridge` and
  :class:`linear_model.RidgeClassifier`.
  :pr:`24465` by :user:`Christian Lorentzen <lorentzenchr>`.

:mod:`sklearn.manifold`
.......................

- |Feature| Adds option to use the normalized stress in :class:`manifold.MDS`. This is
  enabled by setting the new `normalize` parameter to `True`.
  :pr:`10168` by :user:`Łukasz Borchmann <Borchmann>`,
  :pr:`12285` by :user:`Matthias Miltenberger <mattmilten>`,
  :pr:`13042` by :user:`Matthieu Parizy <matthieu-pa>`,
  :pr:`18094` by :user:`Roth E Conrad <rotheconrad>` and
  :pr:`22562` by :user:`Meekail Zain <micky774>`.

- |Enhancement| Adds `eigen_tol` parameter to
  :class:`manifold.SpectralEmbedding`. Both :func:`manifold.spectral_embedding`
  and :class:`manifold.SpectralEmbedding` now propagate `eigen_tol` to all
  choices of `eigen_solver`. Includes a new option `eigen_tol="auto"`
  and begins deprecation to change the default from `eigen_tol=0` to
  `eigen_tol="auto"` in version 1.3.
  :pr:`23210` by :user:`Meekail Zain <micky774>`.

- |Enhancement| :class:`manifold.Isomap` now preserves
  dtype for `np.float32` inputs. :pr:`24714` by :user:`Rahil Parikh <rprkh>`.

- |API| Added an `"auto"` option to the `normalized_stress` argument in
  :class:`manifold.MDS` and :func:`manifold.smacof`. Note that
  `normalized_stress` is only valid for non-metric MDS, therefore the `"auto"`
  option enables `normalized_stress` when `metric=False` and disables it when
  `metric=True`. `"auto"` will become the default value for `normalized_stress`
  in version 1.4.
  :pr:`23834` by :user:`Meekail Zain <micky774>`

:mod:`sklearn.metrics`
......................

- |Feature| :func:`metrics.ConfusionMatrixDisplay.from_estimator`,
  :func:`metrics.ConfusionMatrixDisplay.from_predictions`, and
  :meth:`metrics.ConfusionMatrixDisplay.plot` accepts a `text_kw` parameter which is
  passed to matplotlib's `text` function. :pr:`24051` by `Thomas Fan`_.

- |Feature| :func:`metrics.class_likelihood_ratios` is added to compute the positive and
  negative likelihood ratios derived from the confusion matrix
  of a binary classification problem. :pr:`22518` by
  :user:`Arturo Amor <ArturoAmorQ>`.

- |Feature| Add :class:`metrics.PredictionErrorDisplay` to plot residuals vs
  predicted and actual vs predicted to qualitatively assess the behavior of a
  regressor. The display can be created with the class methods
  :func:`metrics.PredictionErrorDisplay.from_estimator` and
  :func:`metrics.PredictionErrorDisplay.from_predictions`. :pr:`18020` by
  :user:`Guillaume Lemaitre <glemaitre>`.

- |Feature| :func:`metrics.roc_auc_score` now supports micro-averaging
  (`average="micro"`) for the One-vs-Rest multiclass case (`multi_class="ovr"`).
  :pr:`24338` by :user:`Arturo Amor <ArturoAmorQ>`.

- |Enhancement| Adds an `"auto"` option to `eps` in :func:`metrics.log_loss`.
  This option will automatically set the `eps` value depending on the data
  type of `y_pred`. In addition, the default value of `eps` is changed from
  `1e-15` to the new `"auto"` option.
  :pr:`24354` by :user:`Safiuddin Khaja <Safikh>` and :user:`gsiisg <gsiisg>`.

- |Fix| Allows `csr_matrix` as input for parameter: `y_true` of
  the :func:`metrics.label_ranking_average_precision_score` metric.
  :pr:`23442` by :user:`Sean Atukorala <ShehanAT>`

- |Fix| :func:`metrics.ndcg_score` will now trigger a warning when the `y_true`
  value contains a negative value. Users may still use negative values, but the
  result may not be between 0 and 1. Starting in v1.4, passing in negative
  values for `y_true` will raise an error.
  :pr:`22710` by :user:`Conroy Trinh <trinhcon>` and
  :pr:`23461` by :user:`Meekail Zain <micky774>`.

- |Fix| :func:`metrics.log_loss` with `eps=0` now returns a correct value of 0 or
  `np.inf` instead of `nan` for predictions at the boundaries (0 or 1). It also accepts
  integer input.
  :pr:`24365` by :user:`Christian Lorentzen <lorentzenchr>`.

- |API| The parameter `sum_over_features` of
  :func:`metrics.pairwise.manhattan_distances` is deprecated and will be removed in 1.4.
  :pr:`24630` by :user:`Rushil Desai <rusdes>`.

:mod:`sklearn.model_selection`
..............................

- |Feature| Added the class :class:`model_selection.LearningCurveDisplay`
  that allows to make easy plotting of learning curves obtained by the function
  :func:`model_selection.learning_curve`.
  :pr:`24084` by :user:`Guillaume Lemaitre <glemaitre>`.

- |Fix| For all `SearchCV` classes and scipy >= 1.10, rank corresponding to a
  nan score is correctly set to the maximum possible rank, rather than
  `np.iinfo(np.int32).min`. :pr:`24141` by :user:`Loïc Estève <lesteve>`.

- |Fix| In both :class:`model_selection.HalvingGridSearchCV` and
  :class:`model_selection.HalvingRandomSearchCV` parameter
  combinations with a NaN score now share the lowest rank.
  :pr:`24539` by :user:`Tim Head <betatim>`.

- |Fix| For :class:`model_selection.GridSearchCV` and
  :class:`model_selection.RandomizedSearchCV` ranks corresponding to nan
  scores will all be set to the maximum possible rank.
  :pr:`24543` by :user:`Guillaume Lemaitre <glemaitre>`.

:mod:`sklearn.multioutput`
..........................

- |Feature| Added boolean `verbose` flag to classes:
  :class:`multioutput.ClassifierChain` and :class:`multioutput.RegressorChain`.
  :pr:`23977` by :user:`Eric Fiegel <efiegel>`,
  :user:`Chiara Marmo <cmarmo>`,
  :user:`Lucy Liu <lucyleeow>`, and
  :user:`Guillaume Lemaitre <glemaitre>`.

:mod:`sklearn.naive_bayes`
..........................

- |Feature| Add methods `predict_joint_log_proba` to all naive Bayes classifiers.
  :pr:`23683` by :user:`Andrey Melnik <avm19>`.

- |Enhancement| A new parameter `force_alpha` was added to
  :class:`naive_bayes.BernoulliNB`, :class:`naive_bayes.ComplementNB`,
  :class:`naive_bayes.CategoricalNB`, and :class:`naive_bayes.MultinomialNB`,
  allowing user to set parameter alpha to a very small number, greater or equal
  0, which was earlier automatically changed to `1e-10` instead.
  :pr:`16747` by :user:`arka204`,
  :pr:`18805` by :user:`hongshaoyang`,
  :pr:`22269` by :user:`Meekail Zain <micky774>`.

:mod:`sklearn.neighbors`
........................

- |Feature| Adds new function :func:`neighbors.sort_graph_by_row_values` to
  sort a CSR sparse graph such that each row is stored with increasing values.
  This is useful to improve efficiency when using precomputed sparse distance
  matrices in a variety of estimators and avoid an `EfficiencyWarning`.
  :pr:`23139` by `Tom Dupre la Tour`_.

- |Efficiency| :class:`neighbors.NearestCentroid` is faster and requires
  less memory as it better leverages CPUs' caches to compute predictions.
  :pr:`24645` by :user:`Olivier Grisel <ogrisel>`.

- |Enhancement| :class:`neighbors.KernelDensity` bandwidth parameter now accepts
  definition using Scott's and Silverman's estimation methods.
  :pr:`10468` by :user:`Ruben <icfly2>` and :pr:`22993` by
  :user:`Jovan Stojanovic <jovan-stojanovic>`.

- |Enhancement| `neighbors.NeighborsBase` now accepts
  Minkowski semi-metric (i.e. when :math:`0 < p < 1` for
  `metric="minkowski"`) for `algorithm="auto"` or `algorithm="brute"`.
  :pr:`24750` by :user:`Rudresh Veerkhare <RudreshVeerkhare>`

- |Fix| :class:`neighbors.NearestCentroid` now raises an informative error message at fit-time
  instead of failing with a low-level error message at predict-time.
  :pr:`23874` by :user:`Juan Gomez <2357juan>`.

- |Fix| Set `n_jobs=None` by default (instead of `1`) for
  :class:`neighbors.KNeighborsTransformer` and
  :class:`neighbors.RadiusNeighborsTransformer`.
  :pr:`24075` by :user:`Valentin Laurent <Valentin-Laurent>`.

- |Enhancement| :class:`neighbors.LocalOutlierFactor` now preserves
  dtype for `numpy.float32` inputs.
  :pr:`22665` by :user:`Julien Jerphanion <jjerphan>`.

:mod:`sklearn.neural_network`
.............................

- |Fix| :class:`neural_network.MLPClassifier` and
  :class:`neural_network.MLPRegressor` always expose the parameters `best_loss_`,
  `validation_scores_`, and `best_validation_score_`. `best_loss_` is set to
  `None` when `early_stopping=True`, while `validation_scores_` and
  `best_validation_score_` are set to `None` when `early_stopping=False`.
  :pr:`24683` by :user:`Guillaume Lemaitre <glemaitre>`.

:mod:`sklearn.pipeline`
.......................

- |Enhancement| :meth:`pipeline.FeatureUnion.get_feature_names_out` can now
  be used when one of the transformers in the :class:`pipeline.FeatureUnion` is
  `"passthrough"`. :pr:`24058` by :user:`Diederik Perdok <diederikwp>`

- |Enhancement| The :class:`pipeline.FeatureUnion` class now has a `named_transformers`
  attribute for accessing transformers by name.
  :pr:`20331` by :user:`Christopher Flynn <crflynn>`.

:mod:`sklearn.preprocessing`
............................

- |Enhancement| :class:`preprocessing.FunctionTransformer` will always try to set
  `n_features_in_` and `feature_names_in_` regardless of the `validate` parameter.
  :pr:`23993` by `Thomas Fan`_.

- |Fix| :class:`preprocessing.LabelEncoder` correctly encodes NaNs in `transform`.
  :pr:`22629` by `Thomas Fan`_.

- |API| The `sparse` parameter of :class:`preprocessing.OneHotEncoder`
  is now deprecated and will be removed in version 1.4. Use `sparse_output` instead.
  :pr:`24412` by :user:`Rushil Desai <rusdes>`.

:mod:`sklearn.svm`
..................

- |API| The `class_weight_` attribute is now deprecated for
  :class:`svm.NuSVR`, :class:`svm.SVR`, :class:`svm.OneClassSVM`.
  :pr:`22898` by :user:`Meekail Zain <micky774>`.

:mod:`sklearn.tree`
...................

- |Enhancement| :func:`tree.plot_tree`, :func:`tree.export_graphviz` now uses
  a lower case `x[i]` to represent feature `i`. :pr:`23480` by `Thomas Fan`_.

:mod:`sklearn.utils`
....................

- |Feature| A new module exposes development tools to discover estimators (i.e.
  :func:`utils.discovery.all_estimators`), displays (i.e.
  :func:`utils.discovery.all_displays`) and functions (i.e.
  :func:`utils.discovery.all_functions`) in scikit-learn.
  :pr:`21469` by :user:`Guillaume Lemaitre <glemaitre>`.

- |Enhancement| :func:`utils.extmath.randomized_svd` now accepts an argument,
  `lapack_svd_driver`, to specify the lapack driver used in the internal
  deterministic SVD used by the randomized SVD algorithm.
  :pr:`20617` by :user:`Srinath Kailasa <skailasa>`

- |Enhancement| :func:`utils.validation.column_or_1d` now accepts a `dtype`
  parameter to specific `y`'s dtype. :pr:`22629` by `Thomas Fan`_.

- |Enhancement| `utils.extmath.cartesian` now accepts arrays with different
  `dtype` and will cast the output to the most permissive `dtype`.
  :pr:`25067` by :user:`Guillaume Lemaitre <glemaitre>`.

- |Fix| :func:`utils.multiclass.type_of_target` now properly handles sparse matrices.
  :pr:`14862` by :user:`Léonard Binet <leonardbinet>`.

- |Fix| HTML representation no longer errors when an estimator class is a value in
  `get_params`. :pr:`24512` by `Thomas Fan`_.

- |Fix| :func:`utils.estimator_checks.check_estimator` now takes into account
  the `requires_positive_X` tag correctly. :pr:`24667` by `Thomas Fan`_.

- |Fix| :func:`utils.check_array` now supports Pandas Series with `pd.NA`
  by raising a better error message or returning a compatible `ndarray`.
  :pr:`25080` by `Thomas Fan`_.

- |API| The extra keyword parameters of :func:`utils.extmath.density` are deprecated
  and will be removed in 1.4.
  :pr:`24523` by :user:`Mia Bajic <clytaemnestra>`.

.. rubric:: Code and documentation contributors

Thanks to everyone who has contributed to the maintenance and improvement of
the project since version 1.1, including:

2357juan, 3lLobo, Adam J. Stewart, Adam Kania, Adam Li, Aditya Anulekh, Admir
Demiraj, adoublet, Adrin Jalali, Ahmedbgh, Aiko, Akshita Prasanth, Ala-Na,
Alessandro Miola, Alex, Alexandr, Alexandre Perez-Lebel, Alex Buzenet, Ali H.
El-Kassas, aman kumar, Amit Bera, András Simon, Andreas Grivas, Andreas
Mueller, Andrew Wang, angela-maennel, Aniket Shirsat, Anthony22-dev, Antony
Lee, anupam, Apostolos Tsetoglou, Aravindh R, Artur Hermano, Arturo Amor,
as-90, ashah002, Ashwin Mathur, avm19, Azaria Gebremichael, b0rxington, Badr
MOUFAD, Bardiya Ak, Bartłomiej Gońda, BdeGraaff, Benjamin Bossan, Benjamin
Carter, berkecanrizai, Bernd Fritzke, Bhoomika, Biswaroop Mitra, Brandon TH
Chen, Brett Cannon, Bsh, cache-missing, carlo, Carlos Ramos Carreño, ceh,
chalulu, Changyao Chen, Charles Zablit, Chiara Marmo, Christian Lorentzen,
Christian Ritter, Christian Veenhuis, christianwaldmann, Christine P. Chai,
Claudio Salvatore Arcidiacono, Clément Verrier, crispinlogan, Da-Lan,
DanGonite57, Daniela Fernandes, DanielGaerber, darioka, Darren Nguyen,
davidblnc, david-cortes, David Gilbertson, David Poznik, Dayne, Dea María
Léon, Denis, Dev Khant, Dhanshree Arora, Diadochokinetic, diederikwp, Dimitri
Papadopoulos Orfanos, Dimitris Litsidis, drewhogg, Duarte OC, Dwight Lindquist,
Eden Brekke, Edern, Edoardo Abati, Eleanore Denies, EliaSchiavon, Emir,
ErmolaevPA, Fabrizio Damicelli, fcharras, Felipe Siola, Flynn,
francesco-tuveri, Franck Charras, ftorres16, Gael Varoquaux, Geevarghese
George, genvalen, GeorgiaMayDay, Gianr Lazz, Gleb Levitski, Glòria Macià
Muñoz, Guillaume Lemaitre, Guillem García Subies, Guitared, gunesbayir,
Haesun Park, Hansin Ahuja, Hao Chun Chang, Harsh Agrawal, harshit5674,
hasan-yaman, henrymooresc, Henry Sorsky, Hristo Vrigazov, htsedebenham, humahn,
i-aki-y, Ian Thompson, Ido M, Iglesys, Iliya Zhechev, Irene, ivanllt, Ivan
Sedykh, Jack McIvor, jakirkham, JanFidor, Jason G, Jérémie du Boisberranger,
Jiten Sidhpura, jkarolczak, João David, JohnathanPi, John Koumentis, John P,
John Pangas, johnthagen, Jordan Fleming, Joshua Choo Yun Keat, Jovan
Stojanovic, Juan Carlos Alfaro Jiménez, juanfe88, Juan Felipe Arias,
JuliaSchoepp, Julien Jerphanion, jygerardy, ka00ri, Kanishk Sachdev, Kanissh,
Kaushik Amar Das, Kendall, Kenneth Prabakaran, Kento Nozawa, kernc, Kevin
Roice, Kian Eliasi, Kilian Kluge, Kilian Lieret, Kirandevraj, Kraig, krishna
kumar, krishna vamsi, Kshitij Kapadni, Kshitij Mathur, Lauren Burke, Léonard
Binet, lingyi1110, Lisa Casino, Logan Thomas, Loic Esteve, Luciano Mantovani,
Lucy Liu, Maascha, Madhura Jayaratne, madinak, Maksym, Malte S. Kurz, Mansi
Agrawal, Marco Edward Gorelli, Marco Wurps, Maren Westermann, Maria Telenczuk,
Mario Kostelac, martin-kokos, Marvin Krawutschke, Masanori Kanazu, mathurinm,
Matt Haberland, mauroantonioserrano, Max Halford, Maxi Marufo, maximeSaur,
Maxim Smolskiy, Maxwell, m. bou, Meekail Zain, Mehgarg, mehmetcanakbay, Mia
Bajić, Michael Flaks, Michael Hornstein, Michel de Ruiter, Michelle Paradis,
Mikhail Iljin, Misa Ogura, Moritz Wilksch, mrastgoo, Naipawat Poolsawat, Naoise
Holohan, Nass, Nathan Jacobi, Nawazish Alam, Nguyễn Văn Diễn, Nicola
Fanelli, Nihal Thukarama Rao, Nikita Jare, nima10khodaveisi, Nima Sarajpoor,
nitinramvelraj, NNLNR, npache, Nwanna-Joseph, Nymark Kho, o-holman, Olivier
Grisel, Olle Lukowski, Omar Hassoun, Omar Salman, osman tamer, ouss1508,
Oyindamola Olatunji, PAB, Pandata, partev, Paulo Sergio  Soares, Petar
Mlinarić, Peter Jansson, Peter Steinbach, Philipp Jung, Piet Brömmel, Pooja
M, Pooja Subramaniam, priyam kakati, puhuk, Rachel Freeland, Rachit Keerti Das,
Rafal Wojdyla, Raghuveer Bhat, Rahil Parikh, Ralf Gommers, ram vikram singh,
Ravi Makhija, Rehan Guha, Reshama Shaikh, Richard Klima, Rob Crockett, Robert
Hommes, Robert Juergens, Robin Lenz, Rocco Meli, Roman4oo, Ross Barnowski,
Rowan Mankoo, Rudresh Veerkhare, Rushil Desai, Sabri Monaf Sabri, Safikh,
Safiuddin Khaja, Salahuddin, Sam Adam Day, Sandra Yojana Meneses, Sandro
Ephrem, Sangam, SangamSwadik, SANJAI_3, SarahRemus, Sashka Warner, SavkoMax,
Scott Gigante, Scott Gustafson, Sean Atukorala, sec65, SELEE, seljaks, Shady el
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Hida, Shrankhla Srivastava, Shuangchi He, Simon, sonnivs, Sortofamudkip,
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Stéphane Collot, Steven Van Vaerenbergh, Steve Schmerler, Sven Stehle, Tabea
Kossen, TheDevPanda, the-syd-sre, Thijs van Weezel, Thomas Bonald, Thomas
Germer, Thomas J. Fan, Ti-Ion, Tim Head, Timofei Kornev, toastedyeast, Tobias
Pitters, Tom Dupré la Tour, tomiock, Tom Mathews, Tom McTiernan, tspeng, Tyler
Egashira, Valentin Laurent, Varun Jain, Vera Komeyer, Vicente Reyes-Puerta,
Vinayak Mehta, Vincent M, Vishal, Vyom Pathak, wattai, wchathura, WEN Hao,
William M, x110, Xiao Yuan, Xunius, yanhong-zhao-ef, Yusuf Raji, Z Adil Khwaja,
zeeshan lone
