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<section id="version-1-3">
<span id="release-notes-1-3"></span><h1>Version 1.3<a class="headerlink" href="#version-1-3" title="Link to this heading">#</a></h1>
<p>For a short description of the main highlights of the release, please refer to
<a class="reference internal" href="../auto_examples/release_highlights/plot_release_highlights_1_3_0.html#sphx-glr-auto-examples-release-highlights-plot-release-highlights-1-3-0-py"><span class="std std-ref">Release Highlights for scikit-learn 1.3</span></a>.</p>
<p class="rubric">Legend for changelogs</p>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-success">Major Feature</span></span> something big that you couldn’t do before.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-success">Feature</span></span> something that you couldn’t do before.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-info">Efficiency</span></span> an existing feature now may not require as much computation or
memory.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-info">Enhancement</span></span> a miscellaneous minor improvement.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> something that previously didn’t work as documented – or according
to reasonable expectations – should now work.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-warning">API Change</span></span> you will need to change your code to have the same effect in the
future; or a feature will be removed in the future.</p></li>
</ul>
<section id="version-1-3-2">
<span id="changes-1-3-2"></span><h2>Version 1.3.2<a class="headerlink" href="#version-1-3-2" title="Link to this heading">#</a></h2>
<p><strong>October 2023</strong></p>
<section id="changelog">
<h3>Changelog<a class="headerlink" href="#changelog" title="Link to this heading">#</a></h3>
<section id="sklearn-datasets">
<h4><a class="reference internal" href="../api/sklearn.datasets.html#module-sklearn.datasets" title="sklearn.datasets"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.datasets</span></code></a><a class="headerlink" href="#sklearn-datasets" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> All dataset fetchers now accept <code class="docutils literal notranslate"><span class="pre">data_home</span></code> as any object that implements
the <a class="reference external" href="https://docs.python.org/3/library/os.html#os.PathLike" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">os.PathLike</span></code></a> interface, for instance, <a class="reference external" href="https://docs.python.org/3/library/pathlib.html#pathlib.Path" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">pathlib.Path</span></code></a>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27468">#27468</a> by <a class="reference external" href="https://github.com/Charlie-XIAO">Yao Xiao</a>.</p></li>
</ul>
</section>
<section id="sklearn-decomposition">
<h4><a class="reference internal" href="../api/sklearn.decomposition.html#module-sklearn.decomposition" title="sklearn.decomposition"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.decomposition</span></code></a><a class="headerlink" href="#sklearn-decomposition" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Fixes a bug in <a class="reference internal" href="../modules/generated/sklearn.decomposition.KernelPCA.html#sklearn.decomposition.KernelPCA" title="sklearn.decomposition.KernelPCA"><code class="xref py py-class docutils literal notranslate"><span class="pre">decomposition.KernelPCA</span></code></a> by forcing the output of
the internal <a class="reference internal" href="../modules/generated/sklearn.preprocessing.KernelCenterer.html#sklearn.preprocessing.KernelCenterer" title="sklearn.preprocessing.KernelCenterer"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.KernelCenterer</span></code></a> to be a default array. When the
arpack solver is used, it expects an array with a <code class="docutils literal notranslate"><span class="pre">dtype</span></code> attribute.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27583">#27583</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>.</p></li>
</ul>
</section>
<section id="sklearn-metrics">
<h4><a class="reference internal" href="../api/sklearn.metrics.html#module-sklearn.metrics" title="sklearn.metrics"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.metrics</span></code></a><a class="headerlink" href="#sklearn-metrics" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Fixes a bug for metrics using <code class="docutils literal notranslate"><span class="pre">zero_division=np.nan</span></code>
(e.g. <a class="reference internal" href="../modules/generated/sklearn.metrics.precision_score.html#sklearn.metrics.precision_score" title="sklearn.metrics.precision_score"><code class="xref py py-func docutils literal notranslate"><span class="pre">precision_score</span></code></a>) within a paralell loop
(e.g. <a class="reference internal" href="../modules/generated/sklearn.model_selection.cross_val_score.html#sklearn.model_selection.cross_val_score" title="sklearn.model_selection.cross_val_score"><code class="xref py py-func docutils literal notranslate"><span class="pre">cross_val_score</span></code></a>) where the singleton for <code class="docutils literal notranslate"><span class="pre">np.nan</span></code>
will be different in the sub-processes.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27573">#27573</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>.</p></li>
</ul>
</section>
<section id="sklearn-tree">
<h4><a class="reference internal" href="../api/sklearn.tree.html#module-sklearn.tree" title="sklearn.tree"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.tree</span></code></a><a class="headerlink" href="#sklearn-tree" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Do not leak data via non-initialized memory in decision tree pickle files and make
the generation of those files deterministic. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27580">#27580</a> by <a class="reference external" href="https://github.com/lesteve">Loïc Estève</a>.</p></li>
</ul>
</section>
</section>
</section>
<section id="version-1-3-1">
<span id="changes-1-3-1"></span><h2>Version 1.3.1<a class="headerlink" href="#version-1-3-1" title="Link to this heading">#</a></h2>
<p><strong>September 2023</strong></p>
<section id="changed-models">
<h3>Changed models<a class="headerlink" href="#changed-models" title="Link to this heading">#</a></h3>
<p>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.</p>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Ridge models with <code class="docutils literal notranslate"><span class="pre">solver='sparse_cg'</span></code> may have slightly different
results with scipy>=1.12, because of an underlying change in the scipy solver
(see <a class="reference external" href="https://github.com/scipy/scipy/pull/18488">scipy#18488</a> for more
details)
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26814">#26814</a> by <a class="reference external" href="https://github.com/lesteve">Loïc Estève</a></p></li>
</ul>
</section>
<section id="changes-impacting-all-modules">
<h3>Changes impacting all modules<a class="headerlink" href="#changes-impacting-all-modules" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> The <code class="docutils literal notranslate"><span class="pre">set_output</span></code> API correctly works with list input. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27044">#27044</a> by
<a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
</ul>
</section>
<section id="id1">
<h3>Changelog<a class="headerlink" href="#id1" title="Link to this heading">#</a></h3>
<section id="sklearn-calibration">
<h4><a class="reference internal" href="../api/sklearn.calibration.html#module-sklearn.calibration" title="sklearn.calibration"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.calibration</span></code></a><a class="headerlink" href="#sklearn-calibration" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.calibration.CalibratedClassifierCV.html#sklearn.calibration.CalibratedClassifierCV" title="sklearn.calibration.CalibratedClassifierCV"><code class="xref py py-class docutils literal notranslate"><span class="pre">calibration.CalibratedClassifierCV</span></code></a> can now handle models that
produce large prediction scores. Before it was numerically unstable.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26913">#26913</a> by <a class="reference external" href="https://github.com/OmarManzoor">Omar Salman</a>.</p></li>
</ul>
</section>
<section id="sklearn-cluster">
<h4><a class="reference internal" href="../api/sklearn.cluster.html#module-sklearn.cluster" title="sklearn.cluster"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.cluster</span></code></a><a class="headerlink" href="#sklearn-cluster" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.cluster.BisectingKMeans.html#sklearn.cluster.BisectingKMeans" title="sklearn.cluster.BisectingKMeans"><code class="xref py py-class docutils literal notranslate"><span class="pre">cluster.BisectingKMeans</span></code></a> could crash when predicting on data
with a different scale than the data used to fit the model.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27167">#27167</a> by <a class="reference external" href="https://bsky.app/profile/ogrisel.bsky.social">Olivier Grisel</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.cluster.BisectingKMeans.html#sklearn.cluster.BisectingKMeans" title="sklearn.cluster.BisectingKMeans"><code class="xref py py-class docutils literal notranslate"><span class="pre">cluster.BisectingKMeans</span></code></a> now works with data that has a single feature.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27243">#27243</a> by <a class="reference external" href="https://github.com/jeremiedbb">Jérémie du Boisberranger</a>.</p></li>
</ul>
</section>
<section id="sklearn-cross-decomposition">
<h4><a class="reference internal" href="../api/sklearn.cross_decomposition.html#module-sklearn.cross_decomposition" title="sklearn.cross_decomposition"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.cross_decomposition</span></code></a><a class="headerlink" href="#sklearn-cross-decomposition" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.cross_decomposition.PLSRegression.html#sklearn.cross_decomposition.PLSRegression" title="sklearn.cross_decomposition.PLSRegression"><code class="xref py py-class docutils literal notranslate"><span class="pre">cross_decomposition.PLSRegression</span></code></a> now automatically ravels the output
of <code class="docutils literal notranslate"><span class="pre">predict</span></code> if fitted with one dimensional <code class="docutils literal notranslate"><span class="pre">y</span></code>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26602">#26602</a> by <a class="reference external" href="https://github.com/Charlie-XIAO">Yao Xiao</a>.</p></li>
</ul>
</section>
<section id="sklearn-ensemble">
<h4><a class="reference internal" href="../api/sklearn.ensemble.html#module-sklearn.ensemble" title="sklearn.ensemble"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.ensemble</span></code></a><a class="headerlink" href="#sklearn-ensemble" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Fix a bug in <a class="reference internal" href="../modules/generated/sklearn.ensemble.AdaBoostClassifier.html#sklearn.ensemble.AdaBoostClassifier" title="sklearn.ensemble.AdaBoostClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.AdaBoostClassifier</span></code></a> with <code class="docutils literal notranslate"><span class="pre">algorithm="SAMME"</span></code>
where the decision function of each weak learner should be symmetric (i.e.
the sum of the scores should sum to zero for a sample).
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26521">#26521</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>.</p></li>
</ul>
</section>
<section id="sklearn-feature-selection">
<h4><a class="reference internal" href="../api/sklearn.feature_selection.html#module-sklearn.feature_selection" title="sklearn.feature_selection"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.feature_selection</span></code></a><a class="headerlink" href="#sklearn-feature-selection" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.feature_selection.mutual_info_regression.html#sklearn.feature_selection.mutual_info_regression" title="sklearn.feature_selection.mutual_info_regression"><code class="xref py py-func docutils literal notranslate"><span class="pre">feature_selection.mutual_info_regression</span></code></a> now correctly computes the
result when <code class="docutils literal notranslate"><span class="pre">X</span></code> is of integer dtype. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26748">#26748</a> by <a class="reference external" href="https://github.com/Charlie-XIAO">Yao Xiao</a>.</p></li>
</ul>
</section>
<section id="sklearn-impute">
<h4><a class="reference internal" href="../api/sklearn.impute.html#module-sklearn.impute" title="sklearn.impute"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.impute</span></code></a><a class="headerlink" href="#sklearn-impute" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.impute.KNNImputer.html#sklearn.impute.KNNImputer" title="sklearn.impute.KNNImputer"><code class="xref py py-class docutils literal notranslate"><span class="pre">impute.KNNImputer</span></code></a> now correctly adds a missing indicator column in
<code class="docutils literal notranslate"><span class="pre">transform</span></code> when <code class="docutils literal notranslate"><span class="pre">add_indicator</span></code> is set to <code class="docutils literal notranslate"><span class="pre">True</span></code> and missing values are observed
during <code class="docutils literal notranslate"><span class="pre">fit</span></code>. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26600">#26600</a> by <a class="reference external" href="https://github.com/Shreesha3112">Shreesha Kumar Bhat</a>.</p></li>
</ul>
</section>
<section id="id2">
<h4><a class="reference internal" href="../api/sklearn.metrics.html#module-sklearn.metrics" title="sklearn.metrics"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.metrics</span></code></a><a class="headerlink" href="#id2" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Scorers used with <a class="reference internal" href="../modules/generated/sklearn.metrics.get_scorer.html#sklearn.metrics.get_scorer" title="sklearn.metrics.get_scorer"><code class="xref py py-func docutils literal notranslate"><span class="pre">metrics.get_scorer</span></code></a> handle properly
multilabel-indicator matrix.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27002">#27002</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>.</p></li>
</ul>
</section>
<section id="sklearn-mixture">
<h4><a class="reference internal" href="../api/sklearn.mixture.html#module-sklearn.mixture" title="sklearn.mixture"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.mixture</span></code></a><a class="headerlink" href="#sklearn-mixture" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> The initialization of <a class="reference internal" href="../modules/generated/sklearn.mixture.GaussianMixture.html#sklearn.mixture.GaussianMixture" title="sklearn.mixture.GaussianMixture"><code class="xref py py-class docutils literal notranslate"><span class="pre">mixture.GaussianMixture</span></code></a> from user-provided
<code class="docutils literal notranslate"><span class="pre">precisions_init</span></code> for <code class="docutils literal notranslate"><span class="pre">covariance_type</span></code> of <code class="docutils literal notranslate"><span class="pre">full</span></code> or <code class="docutils literal notranslate"><span class="pre">tied</span></code> was not correct,
and has been fixed.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26416">#26416</a> by <a class="reference external" href="https://github.com/mchikyt3">Yang Tao</a>.</p></li>
</ul>
</section>
<section id="sklearn-neighbors">
<h4><a class="reference internal" href="../api/sklearn.neighbors.html#module-sklearn.neighbors" title="sklearn.neighbors"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.neighbors</span></code></a><a class="headerlink" href="#sklearn-neighbors" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.neighbors.KNeighborsClassifier.html#sklearn.neighbors.KNeighborsClassifier.predict" title="sklearn.neighbors.KNeighborsClassifier.predict"><code class="xref py py-meth docutils literal notranslate"><span class="pre">neighbors.KNeighborsClassifier.predict</span></code></a> no longer raises an
exception for <code class="docutils literal notranslate"><span class="pre">pandas.DataFrames</span></code> input.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26772">#26772</a> by <a class="reference external" href="https://github.com/jeremiedbb">Jérémie du Boisberranger</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Reintroduce <code class="docutils literal notranslate"><span class="pre">sklearn.neighbors.BallTree.valid_metrics</span></code> and
<code class="docutils literal notranslate"><span class="pre">sklearn.neighbors.KDTree.valid_metrics</span></code> as public class attributes.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26754">#26754</a> by <a class="reference external" href="https://github.com/jjerphan">Julien Jerphanion</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.model_selection.HalvingRandomSearchCV.html#sklearn.model_selection.HalvingRandomSearchCV" title="sklearn.model_selection.HalvingRandomSearchCV"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.model_selection.HalvingRandomSearchCV</span></code></a> no longer raises
when the input to the <code class="docutils literal notranslate"><span class="pre">param_distributions</span></code> parameter is a list of dicts.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26893">#26893</a> by <a class="reference external" href="https://github.com/StefanieSenger">Stefanie Senger</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Neighbors based estimators now correctly work when <code class="docutils literal notranslate"><span class="pre">metric="minkowski"</span></code> and the
metric parameter <code class="docutils literal notranslate"><span class="pre">p</span></code> is in the range <code class="docutils literal notranslate"><span class="pre">0</span> <span class="pre"><</span> <span class="pre">p</span> <span class="pre"><</span> <span class="pre">1</span></code>, regardless of the <code class="docutils literal notranslate"><span class="pre">dtype</span></code> of <code class="docutils literal notranslate"><span class="pre">X</span></code>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26760">#26760</a> by <a class="reference external" href="https://github.com/Shreesha3112">Shreesha Kumar Bhat</a>.</p></li>
</ul>
</section>
<section id="sklearn-preprocessing">
<h4><a class="reference internal" href="../api/sklearn.preprocessing.html#module-sklearn.preprocessing" title="sklearn.preprocessing"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.preprocessing</span></code></a><a class="headerlink" href="#sklearn-preprocessing" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.preprocessing.LabelEncoder.html#sklearn.preprocessing.LabelEncoder" title="sklearn.preprocessing.LabelEncoder"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.LabelEncoder</span></code></a> correctly accepts <code class="docutils literal notranslate"><span class="pre">y</span></code> as a keyword
argument. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26940">#26940</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.preprocessing.OneHotEncoder.html#sklearn.preprocessing.OneHotEncoder" title="sklearn.preprocessing.OneHotEncoder"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.OneHotEncoder</span></code></a> shows a more informative error message
when <code class="docutils literal notranslate"><span class="pre">sparse_output=True</span></code> and the output is configured to be pandas.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26931">#26931</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
</ul>
</section>
<section id="id3">
<h4><a class="reference internal" href="../api/sklearn.tree.html#module-sklearn.tree" title="sklearn.tree"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.tree</span></code></a><a class="headerlink" href="#id3" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.tree.plot_tree.html#sklearn.tree.plot_tree" title="sklearn.tree.plot_tree"><code class="xref py py-func docutils literal notranslate"><span class="pre">tree.plot_tree</span></code></a> now accepts <code class="docutils literal notranslate"><span class="pre">class_names=True</span></code> as documented.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26903">#26903</a> by <a class="reference external" href="https://github.com/2maz">Thomas Roehr</a></p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> The <code class="docutils literal notranslate"><span class="pre">feature_names</span></code> parameter of <a class="reference internal" href="../modules/generated/sklearn.tree.plot_tree.html#sklearn.tree.plot_tree" title="sklearn.tree.plot_tree"><code class="xref py py-func docutils literal notranslate"><span class="pre">tree.plot_tree</span></code></a> now accepts any kind of
array-like instead of just a list. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27292">#27292</a> by <a class="reference external" href="https://github.com/rprkh">Rahil Parikh</a>.</p></li>
</ul>
</section>
</section>
</section>
<section id="version-1-3-0">
<span id="changes-1-3"></span><h2>Version 1.3.0<a class="headerlink" href="#version-1-3-0" title="Link to this heading">#</a></h2>
<p><strong>June 2023</strong></p>
<section id="id4">
<h3>Changed models<a class="headerlink" href="#id4" title="Link to this heading">#</a></h3>
<p>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.</p>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-info">Enhancement</span></span> <a class="reference internal" href="../modules/generated/sklearn.multiclass.OutputCodeClassifier.html#sklearn.multiclass.OutputCodeClassifier.predict" title="sklearn.multiclass.OutputCodeClassifier.predict"><code class="xref py py-meth docutils literal notranslate"><span class="pre">multiclass.OutputCodeClassifier.predict</span></code></a> now uses a more
efficient pairwise distance reduction. As a consequence, the tie-breaking
strategy is different and thus the predicted labels may be different.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25196">#25196</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-info">Enhancement</span></span> The <code class="docutils literal notranslate"><span class="pre">fit_transform</span></code> method of <a class="reference internal" href="../modules/generated/sklearn.decomposition.DictionaryLearning.html#sklearn.decomposition.DictionaryLearning" title="sklearn.decomposition.DictionaryLearning"><code class="xref py py-class docutils literal notranslate"><span class="pre">decomposition.DictionaryLearning</span></code></a>
is more efficient but may produce different results as in previous versions when
<code class="docutils literal notranslate"><span class="pre">transform_algorithm</span></code> is not the same as <code class="docutils literal notranslate"><span class="pre">fit_algorithm</span></code> and the number of iterations
is small. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/24871">#24871</a> by <a class="reference external" href="https://github.com/OmarManzoor">Omar Salman</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-info">Enhancement</span></span> The <code class="docutils literal notranslate"><span class="pre">sample_weight</span></code> parameter now will be used in centroids
initialization for <a class="reference internal" href="../modules/generated/sklearn.cluster.KMeans.html#sklearn.cluster.KMeans" title="sklearn.cluster.KMeans"><code class="xref py py-class docutils literal notranslate"><span class="pre">cluster.KMeans</span></code></a>, <a class="reference internal" href="../modules/generated/sklearn.cluster.BisectingKMeans.html#sklearn.cluster.BisectingKMeans" title="sklearn.cluster.BisectingKMeans"><code class="xref py py-class docutils literal notranslate"><span class="pre">cluster.BisectingKMeans</span></code></a>
and <a class="reference internal" href="../modules/generated/sklearn.cluster.MiniBatchKMeans.html#sklearn.cluster.MiniBatchKMeans" title="sklearn.cluster.MiniBatchKMeans"><code class="xref py py-class docutils literal notranslate"><span class="pre">cluster.MiniBatchKMeans</span></code></a>.
This change will break backward compatibility, since numbers generated
from same random seeds will be different.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25752">#25752</a> by <a class="reference external" href="https://github.com/glevv">Gleb Levitski</a>,
<a class="reference external" href="https://github.com/jeremiedbb">Jérémie du Boisberranger</a>,
<a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Treat more consistently small values in the <code class="docutils literal notranslate"><span class="pre">W</span></code> and <code class="docutils literal notranslate"><span class="pre">H</span></code> matrices during the
<code class="docutils literal notranslate"><span class="pre">fit</span></code> and <code class="docutils literal notranslate"><span class="pre">transform</span></code> steps of <a class="reference internal" href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="sklearn.decomposition.NMF"><code class="xref py py-class docutils literal notranslate"><span class="pre">decomposition.NMF</span></code></a> and
<a class="reference internal" href="../modules/generated/sklearn.decomposition.MiniBatchNMF.html#sklearn.decomposition.MiniBatchNMF" title="sklearn.decomposition.MiniBatchNMF"><code class="xref py py-class docutils literal notranslate"><span class="pre">decomposition.MiniBatchNMF</span></code></a> which can produce different results than previous
versions. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25438">#25438</a> by <a class="reference external" href="https://github.com/yotamcons">Yotam Avidar-Constantini</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.decomposition.KernelPCA.html#sklearn.decomposition.KernelPCA" title="sklearn.decomposition.KernelPCA"><code class="xref py py-class docutils literal notranslate"><span class="pre">decomposition.KernelPCA</span></code></a> may produce different results through
<code class="docutils literal notranslate"><span class="pre">inverse_transform</span></code> if <code class="docutils literal notranslate"><span class="pre">gamma</span></code> is <code class="docutils literal notranslate"><span class="pre">None</span></code>. Now it will be chosen correctly as
<code class="docutils literal notranslate"><span class="pre">1/n_features</span></code> of the data that it is fitted on, while previously it might be
incorrectly chosen as <code class="docutils literal notranslate"><span class="pre">1/n_features</span></code> of the data passed to <code class="docutils literal notranslate"><span class="pre">inverse_transform</span></code>.
A new attribute <code class="docutils literal notranslate"><span class="pre">gamma_</span></code> is provided for revealing the actual value of <code class="docutils literal notranslate"><span class="pre">gamma</span></code>
used each time the kernel is called.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26337">#26337</a> by <a class="reference external" href="https://github.com/Charlie-XIAO">Yao Xiao</a>.</p></li>
</ul>
</section>
<section id="changed-displays">
<h3>Changed displays<a class="headerlink" href="#changed-displays" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-info">Enhancement</span></span> <a class="reference internal" href="../modules/generated/sklearn.model_selection.LearningCurveDisplay.html#sklearn.model_selection.LearningCurveDisplay" title="sklearn.model_selection.LearningCurveDisplay"><code class="xref py py-class docutils literal notranslate"><span class="pre">model_selection.LearningCurveDisplay</span></code></a> displays both the
train and test curves by default. You can set <code class="docutils literal notranslate"><span class="pre">score_type="test"</span></code> to keep the
past behaviour.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25120">#25120</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.model_selection.ValidationCurveDisplay.html#sklearn.model_selection.ValidationCurveDisplay" title="sklearn.model_selection.ValidationCurveDisplay"><code class="xref py py-class docutils literal notranslate"><span class="pre">model_selection.ValidationCurveDisplay</span></code></a> now accepts passing a
list to the <code class="docutils literal notranslate"><span class="pre">param_range</span></code> parameter.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/27311">#27311</a> by <a class="reference external" href="https://github.com/ArturoAmorQ">Arturo Amor</a>.</p></li>
</ul>
</section>
<section id="id5">
<h3>Changes impacting all modules<a class="headerlink" href="#id5" title="Link to this heading">#</a></h3>
<ul>
<li><p><span class="raw-html"><span class="badge text-bg-info">Enhancement</span></span> The <code class="docutils literal notranslate"><span class="pre">get_feature_names_out</span></code> method of the following classes now
raises a <code class="docutils literal notranslate"><span class="pre">NotFittedError</span></code> if the instance is not fitted. This ensures the error is
consistent in all estimators with the <code class="docutils literal notranslate"><span class="pre">get_feature_names_out</span></code> method.</p>
<ul class="simple">
<li><p><a class="reference internal" href="../modules/generated/sklearn.impute.MissingIndicator.html#sklearn.impute.MissingIndicator" title="sklearn.impute.MissingIndicator"><code class="xref py py-class docutils literal notranslate"><span class="pre">impute.MissingIndicator</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_extraction.DictVectorizer.html#sklearn.feature_extraction.DictVectorizer" title="sklearn.feature_extraction.DictVectorizer"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_extraction.DictVectorizer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_extraction.text.TfidfTransformer.html#sklearn.feature_extraction.text.TfidfTransformer" title="sklearn.feature_extraction.text.TfidfTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_extraction.text.TfidfTransformer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.GenericUnivariateSelect.html#sklearn.feature_selection.GenericUnivariateSelect" title="sklearn.feature_selection.GenericUnivariateSelect"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.GenericUnivariateSelect</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.RFE.html#sklearn.feature_selection.RFE" title="sklearn.feature_selection.RFE"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.RFE</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.RFECV.html#sklearn.feature_selection.RFECV" title="sklearn.feature_selection.RFECV"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.RFECV</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.SelectFdr.html#sklearn.feature_selection.SelectFdr" title="sklearn.feature_selection.SelectFdr"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.SelectFdr</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.SelectFpr.html#sklearn.feature_selection.SelectFpr" title="sklearn.feature_selection.SelectFpr"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.SelectFpr</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.SelectFromModel.html#sklearn.feature_selection.SelectFromModel" title="sklearn.feature_selection.SelectFromModel"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.SelectFromModel</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.SelectFwe.html#sklearn.feature_selection.SelectFwe" title="sklearn.feature_selection.SelectFwe"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.SelectFwe</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="sklearn.feature_selection.SelectKBest"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.SelectKBest</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.SelectPercentile.html#sklearn.feature_selection.SelectPercentile" title="sklearn.feature_selection.SelectPercentile"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.SelectPercentile</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.SequentialFeatureSelector.html#sklearn.feature_selection.SequentialFeatureSelector" title="sklearn.feature_selection.SequentialFeatureSelector"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.SequentialFeatureSelector</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.VarianceThreshold.html#sklearn.feature_selection.VarianceThreshold" title="sklearn.feature_selection.VarianceThreshold"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_selection.VarianceThreshold</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.kernel_approximation.AdditiveChi2Sampler.html#sklearn.kernel_approximation.AdditiveChi2Sampler" title="sklearn.kernel_approximation.AdditiveChi2Sampler"><code class="xref py py-class docutils literal notranslate"><span class="pre">kernel_approximation.AdditiveChi2Sampler</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.impute.IterativeImputer.html#sklearn.impute.IterativeImputer" title="sklearn.impute.IterativeImputer"><code class="xref py py-class docutils literal notranslate"><span class="pre">impute.IterativeImputer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.impute.KNNImputer.html#sklearn.impute.KNNImputer" title="sklearn.impute.KNNImputer"><code class="xref py py-class docutils literal notranslate"><span class="pre">impute.KNNImputer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.impute.SimpleImputer.html#sklearn.impute.SimpleImputer" title="sklearn.impute.SimpleImputer"><code class="xref py py-class docutils literal notranslate"><span class="pre">impute.SimpleImputer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.isotonic.IsotonicRegression.html#sklearn.isotonic.IsotonicRegression" title="sklearn.isotonic.IsotonicRegression"><code class="xref py py-class docutils literal notranslate"><span class="pre">isotonic.IsotonicRegression</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.Binarizer.html#sklearn.preprocessing.Binarizer" title="sklearn.preprocessing.Binarizer"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.Binarizer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.KBinsDiscretizer.html#sklearn.preprocessing.KBinsDiscretizer" title="sklearn.preprocessing.KBinsDiscretizer"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.KBinsDiscretizer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.MaxAbsScaler.html#sklearn.preprocessing.MaxAbsScaler" title="sklearn.preprocessing.MaxAbsScaler"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.MaxAbsScaler</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.MinMaxScaler.html#sklearn.preprocessing.MinMaxScaler" title="sklearn.preprocessing.MinMaxScaler"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.MinMaxScaler</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.Normalizer.html#sklearn.preprocessing.Normalizer" title="sklearn.preprocessing.Normalizer"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.Normalizer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.OrdinalEncoder.html#sklearn.preprocessing.OrdinalEncoder" title="sklearn.preprocessing.OrdinalEncoder"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.OrdinalEncoder</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.PowerTransformer.html#sklearn.preprocessing.PowerTransformer" title="sklearn.preprocessing.PowerTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.PowerTransformer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.QuantileTransformer.html#sklearn.preprocessing.QuantileTransformer" title="sklearn.preprocessing.QuantileTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.QuantileTransformer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.RobustScaler.html#sklearn.preprocessing.RobustScaler" title="sklearn.preprocessing.RobustScaler"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.RobustScaler</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.SplineTransformer.html#sklearn.preprocessing.SplineTransformer" title="sklearn.preprocessing.SplineTransformer"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.SplineTransformer</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.StandardScaler.html#sklearn.preprocessing.StandardScaler" title="sklearn.preprocessing.StandardScaler"><code class="xref py py-class docutils literal notranslate"><span class="pre">preprocessing.StandardScaler</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.random_projection.GaussianRandomProjection.html#sklearn.random_projection.GaussianRandomProjection" title="sklearn.random_projection.GaussianRandomProjection"><code class="xref py py-class docutils literal notranslate"><span class="pre">random_projection.GaussianRandomProjection</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.random_projection.SparseRandomProjection.html#sklearn.random_projection.SparseRandomProjection" title="sklearn.random_projection.SparseRandomProjection"><code class="xref py py-class docutils literal notranslate"><span class="pre">random_projection.SparseRandomProjection</span></code></a></p></li>
</ul>
<p>The <code class="docutils literal notranslate"><span class="pre">NotFittedError</span></code> displays an informative message asking to fit the instance
with the appropriate arguments.</p>
<p><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25294">#25294</a>, <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25308">#25308</a>, <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25291">#25291</a>, <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25367">#25367</a>, <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25402">#25402</a>,
by <a class="reference external" href="https://github.com/jpangas">John Pangas</a>, <a class="reference external" href="https://github.com/rprkh">Rahil Parikh</a> ,
and <a class="reference external" href="https://github.com/albuzenet">Alex Buzenet</a>.</p>
</li>
<li><p><span class="raw-html"><span class="badge text-bg-info">Enhancement</span></span> Added a multi-threaded Cython routine to the compute squared
Euclidean distances (sometimes followed by a fused reduction operation) for a
pair of datasets consisting of a sparse CSR matrix and a dense NumPy.</p>
<p>This can improve the performance of following functions and estimators:</p>
<ul class="simple">
<li><p><a class="reference internal" href="../modules/generated/sklearn.metrics.pairwise_distances_argmin.html#sklearn.metrics.pairwise_distances_argmin" title="sklearn.metrics.pairwise_distances_argmin"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.metrics.pairwise_distances_argmin</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.metrics.pairwise_distances_argmin_min.html#sklearn.metrics.pairwise_distances_argmin_min" title="sklearn.metrics.pairwise_distances_argmin_min"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.metrics.pairwise_distances_argmin_min</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.cluster.AffinityPropagation.html#sklearn.cluster.AffinityPropagation" title="sklearn.cluster.AffinityPropagation"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.cluster.AffinityPropagation</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.cluster.Birch.html#sklearn.cluster.Birch" title="sklearn.cluster.Birch"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.cluster.Birch</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.cluster.MeanShift.html#sklearn.cluster.MeanShift" title="sklearn.cluster.MeanShift"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.cluster.MeanShift</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.cluster.OPTICS.html#sklearn.cluster.OPTICS" title="sklearn.cluster.OPTICS"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.cluster.OPTICS</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.cluster.SpectralClustering.html#sklearn.cluster.SpectralClustering" title="sklearn.cluster.SpectralClustering"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.cluster.SpectralClustering</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.feature_selection.mutual_info_regression.html#sklearn.feature_selection.mutual_info_regression" title="sklearn.feature_selection.mutual_info_regression"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.feature_selection.mutual_info_regression</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.neighbors.KNeighborsClassifier.html#sklearn.neighbors.KNeighborsClassifier" title="sklearn.neighbors.KNeighborsClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.neighbors.KNeighborsClassifier</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.neighbors.KNeighborsRegressor.html#sklearn.neighbors.KNeighborsRegressor" title="sklearn.neighbors.KNeighborsRegressor"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.neighbors.KNeighborsRegressor</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.neighbors.RadiusNeighborsClassifier.html#sklearn.neighbors.RadiusNeighborsClassifier" title="sklearn.neighbors.RadiusNeighborsClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.neighbors.RadiusNeighborsClassifier</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.neighbors.RadiusNeighborsRegressor.html#sklearn.neighbors.RadiusNeighborsRegressor" title="sklearn.neighbors.RadiusNeighborsRegressor"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.neighbors.RadiusNeighborsRegressor</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.neighbors.LocalOutlierFactor.html#sklearn.neighbors.LocalOutlierFactor" title="sklearn.neighbors.LocalOutlierFactor"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.neighbors.LocalOutlierFactor</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.neighbors.NearestNeighbors.html#sklearn.neighbors.NearestNeighbors" title="sklearn.neighbors.NearestNeighbors"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.neighbors.NearestNeighbors</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.manifold.Isomap.html#sklearn.manifold.Isomap" title="sklearn.manifold.Isomap"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.manifold.Isomap</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.manifold.LocallyLinearEmbedding.html#sklearn.manifold.LocallyLinearEmbedding" title="sklearn.manifold.LocallyLinearEmbedding"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.manifold.LocallyLinearEmbedding</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.manifold.TSNE.html#sklearn.manifold.TSNE" title="sklearn.manifold.TSNE"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.manifold.TSNE</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.manifold.trustworthiness.html#sklearn.manifold.trustworthiness" title="sklearn.manifold.trustworthiness"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.manifold.trustworthiness</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.semi_supervised.LabelPropagation.html#sklearn.semi_supervised.LabelPropagation" title="sklearn.semi_supervised.LabelPropagation"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.semi_supervised.LabelPropagation</span></code></a></p></li>
<li><p><a class="reference internal" href="../modules/generated/sklearn.semi_supervised.LabelSpreading.html#sklearn.semi_supervised.LabelSpreading" title="sklearn.semi_supervised.LabelSpreading"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.semi_supervised.LabelSpreading</span></code></a></p></li>
</ul>
<p>A typical example of this performance improvement happens when passing a sparse
CSR matrix to the <code class="docutils literal notranslate"><span class="pre">predict</span></code> or <code class="docutils literal notranslate"><span class="pre">transform</span></code> method of estimators that rely on
a dense NumPy representation to store their fitted parameters (or the reverse).</p>
<p>For instance, <a class="reference internal" href="../modules/generated/sklearn.neighbors.NearestNeighbors.html#sklearn.neighbors.NearestNeighbors.kneighbors" title="sklearn.neighbors.NearestNeighbors.kneighbors"><code class="xref py py-meth docutils literal notranslate"><span class="pre">sklearn.neighbors.NearestNeighbors.kneighbors</span></code></a> is now up
to 2 times faster for this case on commonly available laptops.</p>
<p><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25044">#25044</a> by <a class="reference external" href="https://github.com/jjerphan">Julien Jerphanion</a>.</p>
</li>
<li><p><span class="raw-html"><span class="badge text-bg-info">Enhancement</span></span> All estimators that internally rely on OpenMP multi-threading
(via Cython) now use a number of threads equal to the number of physical
(instead of logical) cores by default. In the past, we observed that using as
many threads as logical cores on SMT hosts could sometimes cause severe
performance problems depending on the algorithms and the shape of the data.
Note that it is still possible to manually adjust the number of threads used
by OpenMP as documented in <a class="reference internal" href="../computing/parallelism.html#parallelism"><span class="std std-ref">Parallelism</span></a>.</p>
<p><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26082">#26082</a> by <a class="reference external" href="https://github.com/jeremiedbb">Jérémie du Boisberranger</a> and
<a class="reference external" href="https://github.com/ogrisel">Olivier Grisel</a>.</p>
</li>
</ul>
</section>
<section id="experimental-under-development">
<h3>Experimental / Under Development<a class="headerlink" href="#experimental-under-development" title="Link to this heading">#</a></h3>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-success">Major Feature</span></span> <a class="reference internal" href="../metadata_routing.html#metadata-routing"><span class="std std-ref">Metadata routing</span></a>’s related base
methods are included in this release. This feature is only available via the
<code class="docutils literal notranslate"><span class="pre">enable_metadata_routing</span></code> feature flag which can be enabled using
<a class="reference internal" href="../modules/generated/sklearn.set_config.html#sklearn.set_config" title="sklearn.set_config"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.set_config</span></code></a> and <a class="reference internal" href="../modules/generated/sklearn.config_context.html#sklearn.config_context" title="sklearn.config_context"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.config_context</span></code></a>. For now this
feature is mostly useful for third party developers to prepare their code
base for metadata routing, and we strongly recommend that they also hide it
behind the same feature flag, rather than having it enabled by default.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/24027">#24027</a> by <a class="reference external" href="https://github.com/adrinjalali">Adrin Jalali</a>, <a class="reference external" href="https://github.com/BenjaminBossan">Benjamin Bossan</a>, and
<a class="reference external" href="https://github.com/OmarManzoor">Omar Salman</a>.</p></li>
</ul>
</section>
<section id="id6">
<h3>Changelog<a class="headerlink" href="#id6" title="Link to this heading">#</a></h3>
<section id="sklearn">
<h4><code class="docutils literal notranslate"><span class="pre">sklearn</span></code><a class="headerlink" href="#sklearn" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-success">Feature</span></span> Added a new option <code class="docutils literal notranslate"><span class="pre">skip_parameter_validation</span></code>, to the function
<a class="reference internal" href="../modules/generated/sklearn.set_config.html#sklearn.set_config" title="sklearn.set_config"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.set_config</span></code></a> and context manager <a class="reference internal" href="../modules/generated/sklearn.config_context.html#sklearn.config_context" title="sklearn.config_context"><code class="xref py py-func docutils literal notranslate"><span class="pre">sklearn.config_context</span></code></a>, that
allows to skip the validation of the parameters passed to the estimators and public
functions. This can be useful to speed up the code but should be used with care
because it can lead to unexpected behaviors or raise obscure error messages when
setting invalid parameters.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25815">#25815</a> by <a class="reference external" href="https://github.com/jeremiedbb">Jérémie du Boisberranger</a>.</p></li>
</ul>
</section>
<section id="sklearn-base">
<h4><a class="reference internal" href="../api/sklearn.base.html#module-sklearn.base" title="sklearn.base"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.base</span></code></a><a class="headerlink" href="#sklearn-base" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-success">Feature</span></span> A <code class="docutils literal notranslate"><span class="pre">__sklearn_clone__</span></code> protocol is now available to override the
default behavior of <a class="reference internal" href="../modules/generated/sklearn.base.clone.html#sklearn.base.clone" title="sklearn.base.clone"><code class="xref py py-func docutils literal notranslate"><span class="pre">base.clone</span></code></a>. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/24568">#24568</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.base.TransformerMixin.html#sklearn.base.TransformerMixin" title="sklearn.base.TransformerMixin"><code class="xref py py-class docutils literal notranslate"><span class="pre">base.TransformerMixin</span></code></a> now currently keeps a namedtuple’s class
if <code class="docutils literal notranslate"><span class="pre">transform</span></code> returns a namedtuple. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/26121">#26121</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
</ul>
</section>
<section id="id7">
<h4><a class="reference internal" href="../api/sklearn.calibration.html#module-sklearn.calibration" title="sklearn.calibration"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.calibration</span></code></a><a class="headerlink" href="#id7" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> <a class="reference internal" href="../modules/generated/sklearn.calibration.CalibratedClassifierCV.html#sklearn.calibration.CalibratedClassifierCV" title="sklearn.calibration.CalibratedClassifierCV"><code class="xref py py-class docutils literal notranslate"><span class="pre">calibration.CalibratedClassifierCV</span></code></a> now does not enforce sample
alignment on <code class="docutils literal notranslate"><span class="pre">fit_params</span></code>. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/25805">#25805</a> by <a class="reference external" href="https://github.com/adrinjalali">Adrin Jalali</a>.</p></li>