scikit-learn · glemaitre · Dec 24, 2021 · Dec 24, 2021 · Dec 24, 2021 · Dec 24, 2021
diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
@@ -24,7 +24,14 @@ Changelog
 
 - |Fix| Fixed an infinite loop in :func:`cluster.SpectralClustering` by
   moving an iteration counter from try to except.
-  :pr:`21271` by :user:`Tyler Martin <martintb>`
+  :pr:`21271` by :user:`Tyler Martin <martintb>`.
+
+:mod:`sklearn.datasets`
+.......................
+
+- |Fix| :func:`datasets.fetch_openml` is now thread safe. Data is first
+  downloaded to a temporary subfolder and then renamed.
+  :pr:`21833` by :user:`Siavash Rezazadeh <siavrez>`.
 
 :mod:`sklearn.decomposition`
 ............................
@@ -35,13 +42,45 @@ Changelog
   and :class:`decomposition.MiniBatchSparsePCA` to be convex and match the referenced
   article. :pr:`19210` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
 
+:mod:`sklearn.ensemble`
+.......................
+
+- |Fix| :class:`ensemble.RandomForestClassifier`,
+  :class:`ensemble.RandomForestRegressor`,
+  :class:`ensemble.ExtraTreesClassifier`, :class:`ensemble.ExtraTreesRegressor`,
+  and :class:`ensemble.RandomTreesEmbedding` now raise a ``ValueError`` when
+  ``bootstrap=False`` and ``max_samples`` is not ``None``.
+  :pr:`21295` :user:`Haoyin Xu <PSSF23>`.
+
+- |Fix| Solve a bug in :class:`ensemble.GradientBoostingClassifier` where the
+  exponential loss was computing the positive gradient instead of the
+  negative one.
+  :pr:`22050` by :user:`Guillaume Lemaitre <glemaitre>`.
+
 :mod:`sklearn.feature_selection`
 ................................
 
 - |Fix| Fixed :class:`feature_selection.SelectFromModel` by improving support
   for base estimators that do not set `feature_names_in_`. :pr:`21991` by
   `Thomas Fan`_.
 
+:mod:`sklearn.impute`
+.....................
+
+- |Fix| Fix a bug in :class:`linear_model.RidgeClassifierCV` where the method
+  `predict` was performing an `argmax` on the scores obtained from
+  `decision_function` instead of returning the multilabel indicator matrix.
+  :pr:`19869` by :user:`Guillaume Lemaitre <glemaitre>`.
+
+:mod:`sklearn.linear_model`
+...........................
+
+- |Fix| :class:`linear_model.LassoLarsIC` now correctly computes AIC
+  and BIC. An error is now raised when `n_features > n_samples` and
+  when the noise variance is not provided.
+  :pr:`21481` by :user:`Guillaume Lemaitre <glemaitre>` and
+  :user:`Andrés Babino <ababino>`.
+
 :mod:`sklearn.manifold`
 .......................
 
@@ -83,12 +122,25 @@ Changelog
 - |Fix| Fixes compatibility bug with NumPy 1.22 in :class:`preprocessing.OneHotEncoder`.
   :pr:`21517` by `Thomas Fan`_.
 
+:mod:`sklearn.svm`
+..................
+
+- |Fix| :class:`smv.NuSVC`, :class:`svm.NuSVR`, :class:`svm.SVC`,
+  :class:`svm.SVR`, :class:`svm.OneClassSVM` now validate input
+  parameters in `fit` instead of `__init__`.
+  :pr:`21436` by :user:`Haidar Almubarak <Haidar13 >`.
+
 :mod:`sklearn.tree`
 ...................
 
 - |Fix| Prevents :func:`tree.plot_tree` from drawing out of the boundary of
   the figure. :pr:`21917` by `Thomas Fan`_.
 
+- |Fix| Support loading pickles of decision tree models when the pickle has
+  been generated on a platform with a different bitness. A typical example is
+  to train and pickle the model on 64 bit machine and load the model on a 32
+  bit machine for prediction. :pr:`21552` by :user:`Loïc Estève <lesteve>`.
+
 :mod:`sklearn.utils`
 ....................
 

diff --git a/doc/whats_new/v1.1.rst b/doc/whats_new/v1.1.rst
@@ -117,10 +117,6 @@ Changelog
   hole; when set to True, it returns the swiss-hole dataset. :pr:`21482` by
   :user:`Sebastian Pujalte <pujaltes>`.
 
-- |Fix| :func:`datasets.fetch_openml` is now thread safe. Data is first downloaded
-  to a temporary subfolder and then renamed.
-  :pr:`21833` by :user:`Siavash Rezazadeh <siavrez>`.
-
 - |Enhancement| :func:`datasets.load_diabetes` now accepts the parameter
   ``scaled``, to allow loading unscaled data. The scaled version of this
   dataset is now computed from the unscaled data, and can produce slightly
@@ -141,18 +137,6 @@ Changelog
   get accurate results when the number of features is large.
   :pr:`21109` by :user:`Smile <x-shadow-man>`.
 
-- |Fix| :class:`decomposition.FastICA` now validates input parameters in `fit` instead of `__init__`.
-  :pr:`21432` by :user:`Hannah Bohle <hhnnhh>` and :user:`Maren Westermann <marenwestermann>`.
-
-- |Fix| :class:`decomposition.FactorAnalysis` now validates input parameters
-  in `fit` instead of `__init__`.
-  :pr:`21713` by :user:`Haya <HayaAlmutairi>` and
-  :user:`Krum Arnaudov <krumeto>`.
-
-- |Fix| :class:`decomposition.KernelPCA` now validates input parameters in
-  `fit` instead of `__init__`.
-  :pr:`21567` by :user:`Maggie Chege <MaggieChege>`.
-
 - |API| Adds :term:`get_feature_names_out` to all transformers in the
   :mod:`~sklearn.decomposition` module:
   :class:`~sklearn.decomposition.DictionaryLearning`,
@@ -169,39 +153,23 @@ Changelog
   and :class:`~sklearn.decomposition.TruncatedSVD`. :pr:`21334` by
   `Thomas Fan`_.
 
-:mod:`sklearn.feature_extraction`
-.................................
-
-- |Fix| :class:`feature_extraction.FeatureHasher` now validates input parameters
-  in `transform` instead of `__init__`. :pr:`21573` by
-  :user:`Hannah Bohle <hhnnhh>` and :user:`Maren Westermann <marenwestermann>`.
-
-- |API| :func:`decomposition.FastICA` now supports unit variance for whitening.
-  The default value of its `whiten` argument will change from `True`
-  (which behaves like `'arbitrary-variance'`) to `'unit-variance'` in version 1.3.
-  :pr:`19490` by :user:`Facundo Ferrin <fferrin>` and :user:`Julien Jerphanion <jjerphan>`
+- |Fix| :class:`decomposition.FastICA` now validates input parameters in `fit`
+  instead of `__init__`.
+  :pr:`21432` by :user:`Hannah Bohle <hhnnhh>` and
+  :user:`Maren Westermann <marenwestermann>`.
 
-:mod:`sklearn.feature_selection`
-................................
+- |Fix| :class:`decomposition.FactorAnalysis` now validates input parameters
+  in `fit` instead of `__init__`.
+  :pr:`21713` by :user:`Haya <HayaAlmutairi>` and
+  :user:`Krum Arnaudov <krumeto>`.
 
-- |Enhancement| Add a parameter `force_finite` to
-  :func:`feature_selection.f_regression` and
-  :func:`feature_selection.r_regression`. This parameter allows to force the
-  output to be finite in the case where a feature or a the target is constant
-  or that the feature and target are perfectly correlated (only for the
-  F-statistic).
-  :pr:`17819` by :user:`Juan Carlos Alfaro Jiménez <alfaro96>`.
+- |Fix| :class:`decomposition.KernelPCA` now validates input parameters in
+  `fit` instead of `__init__`.
+  :pr:`21567` by :user:`Maggie Chege <MaggieChege>`.
 
 :mod:`sklearn.ensemble`
 .......................
 
-- |Fix| :class:`ensemble.RandomForestClassifier`,
-  :class:`ensemble.RandomForestRegressor`,
-  :class:`ensemble.ExtraTreesClassifier`, :class:`ensemble.ExtraTreesRegressor`,
-  and :class:`ensemble.RandomTreesEmbedding` now raise a ``ValueError`` when
-  ``bootstrap=False`` and ``max_samples`` is not ``None``.
-  :pr:`21295` :user:`Haoyin Xu <PSSF23>`.
-
 - |API| Changed the default of :func:`max_features` to 1.0 for
   :class:`ensemble.RandomForestRegressor` and to `"sqrt"` for
   :class:`ensemble.RandomForestClassifier`. Note that these give the same fit
@@ -211,10 +179,18 @@ Changelog
   :class:`ensemble.ExtraTreesClassifier`.
   :pr:`20803` by :user:`Brian Sun <bsun94>`.
 
-- |Fix| Solve a bug in :class:`ensemble.GradientBoostingClassifier` where the
-  exponential loss was computing the positive gradient instead of the
-  negative one.
-  :pr:`22050` by :user:`Guillaume Lemaitre <glemaitre>`.
+:mod:`sklearn.feature_extraction`
+.................................
+
+- |API| :func:`decomposition.FastICA` now supports unit variance for whitening.
+  The default value of its `whiten` argument will change from `True`
+  (which behaves like `'arbitrary-variance'`) to `'unit-variance'` in version 1.3.
+  :pr:`19490` by :user:`Facundo Ferrin <fferrin>` and
+  :user:`Julien Jerphanion <jjerphan>`.
+
+- |Fix| :class:`feature_extraction.FeatureHasher` now validates input parameters
+  in `transform` instead of `__init__`. :pr:`21573` by
+  :user:`Hannah Bohle <hhnnhh>` and :user:`Maren Westermann <marenwestermann>`.
 
 :mod:`sklearn.feature_extraction.text`
 ......................................
@@ -224,6 +200,17 @@ Changelog
   by our API.
   :pr:`21832` by :user:`Guillaume Lemaitre <glemaitre>`.
 
+:mod:`sklearn.feature_selection`
+................................
+
+- |Enhancement| Add a parameter `force_finite` to
+  :func:`feature_selection.f_regression` and
+  :func:`feature_selection.r_regression`. This parameter allows to force the
+  output to be finite in the case where a feature or a the target is constant
+  or that the feature and target are perfectly correlated (only for the
+  F-statistic).
+  :pr:`17819` by :user:`Juan Carlos Alfaro Jiménez <alfaro96>`.
+
 :mod:`sklearn.impute`
 .....................
 
@@ -244,11 +231,6 @@ Changelog
   values in the training set.
   :pr:`21617` by :user:`Christian Ritter <chritter>`.
 
-- |Fix| Fix a bug in :class:`linear_model.RidgeClassifierCV` where the method
-  `predict` was performing an `argmax` on the scores obtained from
-  `decision_function` instead of returning the multilabel indicator matrix.
-  :pr:`19869` by :user:`Guillaume Lemaitre <glemaitre>`.
-
 - |Enhancement| :class:`linear_model.RidgeClassifier` is now supporting
   multilabel classification.
   :pr:`19689` by :user:`Guillaume Lemaitre <glemaitre>`.
@@ -276,12 +258,6 @@ Changelog
   for the highs based solvers.
   :pr:`21086` by :user:`Venkatachalam Natchiappan <venkyyuvy>`.
 
-- |Fix| :class:`linear_model.LassoLarsIC` now correctly computes AIC
-  and BIC. An error is now raised when `n_features > n_samples` and
-  when the noise variance is not provided.
-  :pr:`21481` by :user:`Guillaume Lemaitre <glemaitre>` and
-  :user:`Andrés Babino <ababino>`.
-
 :mod:`sklearn.metrics`
 ......................
 
@@ -293,7 +269,7 @@ Changelog
 
 - |API| Parameters ``sample_weight`` and ``multioutput`` of :func:`metrics.
   mean_absolute_percentage_error` are now keyword-only, in accordance with `SLEP009
-  <https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep009/proposal.html>`.
+  <https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep009/proposal.html>`_.
   A deprecation cycle was introduced.
   :pr:`21576` by :user:`Paul-Emile Dugnat <pedugnat>`.
 
@@ -317,9 +293,10 @@ Changelog
   splits failed. Similarly raise an error during grid-search when the fits for
   all the models and all the splits failed. :pr:`21026` by :user:`Loïc Estève <lesteve>`.
 
-- |Fix| :class:`model_selection.GridSearchCV`, :class:`model_selection.HalvingGridSearchCV`
-   now validate input parameters in `fit` instead of `__init__`.
-   :pr:`21880` by :user:`Mrinal Tyagi <MrinalTyagi>`.
+- |Fix| :class:`model_selection.GridSearchCV`,
+  :class:`model_selection.HalvingGridSearchCV`
+  now validate input parameters in `fit` instead of `__init__`.
+  :pr:`21880` by :user:`Mrinal Tyagi <MrinalTyagi>`.
 
 :mod:`sklearn.mixture`
 ......................
@@ -329,23 +306,33 @@ Changelog
   its square root.
   :pr:`22058` by :user:`Guillaume Lemaitre <glemaitre>`.
 
+:mod:`sklearn.neighbors`
+........................
+
+- |Enhancement| `utils.validation.check_array` and `utils.validation.type_of_target`
+  now accept an `input_name` parameter to make the error message more
+  informative when passed invalid input data (e.g. with NaN or infinite
+  values).
+  :pr:`21219` by :user:`Olivier Grisel <ogrisel>`.
+
+- |Enhancement| :func:`utils.validation.check_array` returns a float
+  ndarray with `np.nan` when passed a `Float32` or `Float64` pandas extension
+  array with `pd.NA`. :pr:`21278` by `Thomas Fan`_.
+
+- |Fix| :class:`neighbors.KernelDensity` now validates input parameters in `fit`
+  instead of `__init__`. :pr:`21430` by :user:`Desislava Vasileva <DessyVV>` and
+  :user:`Lucy Jimenez <LucyJimenez>`.
+
 :mod:`sklearn.pipeline`
 .......................
 
 - |Enhancement| Added support for "passthrough" in :class:`FeatureUnion`.
   Setting a transformer to "passthrough" will pass the features unchanged.
   :pr:`20860` by :user:`Shubhraneel Pal <shubhraneel>`.
 
-:mod:`sklearn.svm`
-...................
-
-- |Enhancement| :class:`svm.OneClassSVM`, :class:`svm.NuSVC`,
-  :class:`svm.NuSVR`, :class:`svm.SVC` and :class:`svm.SVR` now expose
-  `n_iter_`, the number of iterations of the libsvm optimization routine.
-  :pr:`21408` by :user:`Juan Martín Loyola <jmloyola>`.
-- |Fix| :class: `pipeline.Pipeline` now does not validate hyper-parameters in
+- |Fix| :class:`pipeline.Pipeline` now does not validate hyper-parameters in
   `__init__` but in `.fit()`.
-  :pr:`21888` by :user:`iofall <iofall>` and :user: `Arisa Y. <arisayosh>`.
+  :pr:`21888` by :user:`iofall <iofall>` and :user:`Arisa Y. <arisayosh>`.
 
 :mod:`sklearn.preprocessing`
 ............................
@@ -355,10 +342,6 @@ Changelog
   the model. The option is only available when `strategy` is set to `quantile`.
   :pr:`21445` by :user:`Felipe Bidu <fbidu>` and :user:`Amanda Dsouza <amy12xx>`.
 
-- |Fix| :class:`preprocessing.LabelBinarizer` now validates input parameters in `fit`
-  instead of `__init__`.
-  :pr:`21434` by :user:`Krum Arnaudov <krumeto>`.
-
 - |Enhancement| Added the `get_feature_names_out` method and a new parameter
   `feature_names_out` to :class:`preprocessing.FunctionTransformer`. You can set
   `feature_names_out` to 'one-to-one' to use the input features names as the
@@ -368,13 +351,26 @@ Changelog
   then `get_output_feature_names` is not defined.
   :pr:`21569` by :user:`Aurélien Geron <ageron>`.
 
+- |Fix| :class:`preprocessing.LabelBinarizer` now validates input parameters in
+  `fit` instead of `__init__`.
+  :pr:`21434` by :user:`Krum Arnaudov <krumeto>`.
+
+:mod:`sklearn.random_projection`
+................................
+
+- |API| Adds :term:`get_feature_names_out` to all transformers in the
+  :mod:`~sklearn.random_projection` module:
+  :class:`~sklearn.random_projection.GaussianRandomProjection` and
+  :class:`~sklearn.random_projection.SparseRandomProjection`. :pr:`21330` by
+  :user:`Loïc Estève <lesteve>`.
+
 :mod:`sklearn.svm`
 ..................
 
-- |Fix| :class:`smv.NuSVC`, :class:`svm.NuSVR`, :class:`svm.SVC`,
-  :class:`svm.SVR`, :class:`svm.OneClassSVM` now validate input
-  parameters in `fit` instead of `__init__`.
-  :pr:`21436` by :user:`Haidar Almubarak <Haidar13 >`.
+- |Enhancement| :class:`svm.OneClassSVM`, :class:`svm.NuSVC`,
+  :class:`svm.NuSVR`, :class:`svm.SVC` and :class:`svm.SVR` now expose
+  `n_iter_`, the number of iterations of the libsvm optimization routine.
+  :pr:`21408` by :user:`Juan Martín Loyola <jmloyola>`.
 
 :mod:`sklearn.utils`
 ....................
@@ -387,40 +383,6 @@ Changelog
   left corner of the HTML representation to show how the elements are
   clickable. :pr:`21298` by `Thomas Fan`_.
 
-:mod:`sklearn.neighbors`
-........................
-
-- |Fix| :class:`neighbors.KernelDensity` now validates input parameters in `fit`
-  instead of `__init__`. :pr:`21430` by :user:`Desislava Vasileva <DessyVV>` and
-  :user:`Lucy Jimenez <LucyJimenez>`.
-
-- |Enhancement| `utils.validation.check_array` and `utils.validation.type_of_target`
-  now accept an `input_name` parameter to make the error message more
-  informative when passed invalid input data (e.g. with NaN or infinite
-  values).
-  :pr:`21219` by :user:`Olivier Grisel <ogrisel>`.
-
-- |Enhancement| :func:`utils.validation.check_array` returns a float
-  ndarray with `np.nan` when passed a `Float32` or `Float64` pandas extension
-  array with `pd.NA`. :pr:`21278` by `Thomas Fan`_.
-
-:mod:`sklearn.random_projection`
-................................
-
-- |API| Adds :term:`get_feature_names_out` to all transformers in the
-  :mod:`~sklearn.random_projection` module:
-  :class:`~sklearn.random_projection.GaussianRandomProjection` and
-  :class:`~sklearn.random_projection.SparseRandomProjection`. :pr:`21330` by
-  :user:`Loïc Estève <lesteve>`.
-
-:mod:`sklearn.tree`
-...................
-
-- |Fix| Support loading pickles of decision tree models when the pickle has
-  been generated on a platform with a different bitness. A typical example is
-  to train and pickle the model on 64 bit machine and load the model on a 32
-  bit machine for prediction. :pr:`21552` by :user:`Loïc Estève <lesteve>`.
-
 Code and Documentation Contributors
 -----------------------------------