DOC update changelog for 1.4.1 release (#28413)

doc/templates/index.html

@@ -169,6 +169,8 @@ <h4 class="sk-landing-call-header">News</h4>
         <li><strong>On-going development:</strong>
         <a href="whats_new/v1.5.html#version-1-5-0">scikit-learn 1.5 (Changelog)</a>
         </li>
+        <li><strong>February 2024.</strong> scikit-learn 1.4.1 is available for download (<a href="whats_new/v1.4.html#version-1-4-1">Changelog</a>).
+        </li>
         <li><strong>January 2024.</strong> scikit-learn 1.4.0 is available for download (<a href="whats_new/v1.4.html#version-1-4-0">Changelog</a>).
         </li>
         <li><strong>October 2023.</strong> scikit-learn 1.3.2 is available for download (<a href="whats_new/v1.3.html#version-1-3-2">Changelog</a>).

doc/whats_new/v1.4.rst

@@ -18,7 +18,7 @@ For a short description of the main highlights of the release, please refer to
 Version 1.4.1
 =============
 
-**In Development**
+**February 2024**
 
 Metadata Routing
 ----------------
@@ -34,15 +34,16 @@ Metadata Routing
 DataFrame Support
 -----------------
 
-- |Enhancement| Pandas and Polars dataframe are validated directly without ducktyping
-  checks. :pr:`28195` by `Thomas Fan`_.
+- |Enhancement| |Fix| Pandas and Polars dataframe are validated directly without
+  ducktyping checks.
+  :pr:`28195` by `Thomas Fan`_.
 
-Changes impacting all modules
------------------------------
+Changes impacting many modules
+------------------------------
 
-- Partial revert of :pr:`28191` to avoid a performance regression for estimators
-  relying on euclidean pairwise computation with sparse matrices. The impacted
-  estimators are:
+- |Efficiency| |Fix| Partial revert of :pr:`28191` to avoid a performance regression for
+  estimators relying on euclidean pairwise computation with
+  sparse matrices. The impacted estimators are:
 
   - :func:`sklearn.metrics.pairwise_distances_argmin`
   - :func:`sklearn.metrics.pairwise_distances_argmin_min`
@@ -66,6 +67,15 @@ Changes impacting all modules
   columns of the returned dataframe.
   :pr:`28262` by :user:`Guillaume Lemaitre <glemaitre>`.
 
+- |Fix| When users try to use a method in :class:`~ensemble.StackingClassifier`,
+  :class:`~ensemble.StackingClassifier`, :class:`~ensemble.StackingClassifier`,
+  :class:`~feature_selection.SelectFromModel`, :class:`~feature_selection.RFE`,
+  :class:`~semi_supervised.SelfTrainingClassifier`,
+  :class:`~multiclass.OneVsOneClassifier`, :class:`~multiclass.OutputCodeClassifier` or
+  :class:`~multiclass.OneVsRestClassifier` that their sub-estimators don't implement,
+  the `AttributeError` now reraises in the traceback.
+  :pr:`28167` by :user:`Stefanie Senger <StefanieSenger>`.
+
 Metadata Routing
 ----------------
 
@@ -134,44 +144,42 @@ Changelog
 
 - |Fix| make :class:`preprocessing.FunctionTransformer` more lenient and overwrite
   output column names with the `get_feature_names_out` in the following cases:
-
-  - the input and output column names remain the same (happen when using NumPy `ufunc`);
-  - the input column names are numbers;
-  - the output will be set to Pandas or Polars dataframe.
-
+  (i) the input and output column names remain the same (happen when using NumPy
+  `ufunc`); (ii) the input column names are numbers; (iii) the output will be set to
+  Pandas or Polars dataframe.
   :pr:`28241` by :user:`Guillaume Lemaitre <glemaitre>`.
 
 - |Fix| :class:`preprocessing.FunctionTransformer` now also warns when `set_output`
   is called with `transform="polars"` and `func` does not return a Polars dataframe or
   `feature_names_out` is not specified.
   :pr:`28263` by :user:`Guillaume Lemaitre <glemaitre>`.
 
+- |Fix| :class:`preprocessing.TargetEncoder` no longer fails when
+  `target_type="continuous"` and the input is read-only. In particular, it now
+  works with pandas copy-on-write mode enabled.
+  :pr:`28233` by :user:`John Hopfensperger <s-banach>`.
+
 :mod:`sklearn.tree`
 ...................
 
 - |Fix| :class:`tree.DecisionTreeClassifier` and
   :class:`tree.DecisionTreeRegressor` are handling missing values properly. The internal
-  criterion was not initialize when no missing values were present in the data, leading
+  criterion was not initialized when no missing values were present in the data, leading
   to potentially wrong criterion values.
   :pr:`28295` by :user:`Guillaume Lemaitre <glemaitre>` and
   :pr:`28327` by :user:`Adam Li <adam2392>`.
 
 :mod:`sklearn.utils`
 ....................
 
+- |Enhancement| |Fix| :func:`utils.metaestimators.available_if` now reraises the error
+  from the `check` function as the cause of the `AttributeError`.
+  :pr:`28198` by `Thomas Fan`_.
+
 - |Fix| :func:`utils._safe_indexing` now raises a `ValueError` when `X` is a Python list
   and `axis=1`, as documented in the docstring.
   :pr:`28222` by :user:`Guillaume Lemaitre <glemaitre>`.
 
-
-:mod:`sklearn.preprocessing`
-............................
-
-- |Fix| :class:`preprocessing.TargetEncoder` no longer fails when
-  `target_type="continuous"` and the input is read-only. In particular, it now
-  works with pandas copy-on-write mode enabled.
-  :pr:`28233` by :user:`John Hopfensperger <s-banach>`.
-
 .. _changes_1_4:
 
 Version 1.4.0