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<section id="version-1-0">
<span id="release-notes-1-0"></span><h1>Version 1.0<a class="headerlink" href="#version-1-0" 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_0_0.html#sphx-glr-auto-examples-release-highlights-plot-release-highlights-1-0-0-py"><span class="std std-ref">Release Highlights for scikit-learn 1.0</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-1-0-2">
<span id="changes-1-0-2"></span><h2>Version 1.0.2<a class="headerlink" href="#version-1-0-2" title="Link to this heading">#</a></h2>
<p><strong>December 2021</strong></p>
<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.Birch.html#sklearn.cluster.Birch" title="sklearn.cluster.Birch"><code class="xref py py-class docutils literal notranslate"><span class="pre">cluster.Birch</span></code></a>,
<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>, <a class="reference internal" href="../modules/generated/sklearn.ensemble.RandomForestRegressor.html#sklearn.ensemble.RandomForestRegressor" title="sklearn.ensemble.RandomForestRegressor"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.RandomForestRegressor</span></code></a>,
<a class="reference internal" href="../modules/generated/sklearn.ensemble.RandomForestClassifier.html#sklearn.ensemble.RandomForestClassifier" title="sklearn.ensemble.RandomForestClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.RandomForestClassifier</span></code></a>,
<a class="reference internal" href="../modules/generated/sklearn.ensemble.GradientBoostingRegressor.html#sklearn.ensemble.GradientBoostingRegressor" title="sklearn.ensemble.GradientBoostingRegressor"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.GradientBoostingRegressor</span></code></a>, and
<a class="reference internal" href="../modules/generated/sklearn.ensemble.GradientBoostingClassifier.html#sklearn.ensemble.GradientBoostingClassifier" title="sklearn.ensemble.GradientBoostingClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.GradientBoostingClassifier</span></code></a> do not raise warning when fitted
on a pandas DataFrame anymore. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21578">#21578</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
</ul>
<section id="changelog">
<h3>Changelog<a class="headerlink" href="#changelog" title="Link to this heading">#</a></h3>
<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> Fixed an infinite loop in <a class="reference internal" href="../modules/generated/sklearn.cluster.SpectralClustering.html#sklearn.cluster.SpectralClustering" title="sklearn.cluster.SpectralClustering"><code class="xref py py-func docutils literal notranslate"><span class="pre">cluster.SpectralClustering</span></code></a> by
moving an iteration counter from try to except.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21271">#21271</a> by <a class="reference external" href="https://github.com/martintb">Tyler Martin</a>.</p></li>
</ul>
</section>
<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> <a class="reference internal" href="../modules/generated/sklearn.datasets.fetch_openml.html#sklearn.datasets.fetch_openml" title="sklearn.datasets.fetch_openml"><code class="xref py py-func docutils literal notranslate"><span class="pre">datasets.fetch_openml</span></code></a> is now thread safe. Data is first
downloaded to a temporary subfolder and then renamed.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21833">#21833</a> by <a class="reference external" href="https://github.com/siavrez">Siavash Rezazadeh</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> Fixed the constraint on the objective function 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>,
<a class="reference internal" href="../modules/generated/sklearn.decomposition.MiniBatchDictionaryLearning.html#sklearn.decomposition.MiniBatchDictionaryLearning" title="sklearn.decomposition.MiniBatchDictionaryLearning"><code class="xref py py-class docutils literal notranslate"><span class="pre">decomposition.MiniBatchDictionaryLearning</span></code></a>, <a class="reference internal" href="../modules/generated/sklearn.decomposition.SparsePCA.html#sklearn.decomposition.SparsePCA" title="sklearn.decomposition.SparsePCA"><code class="xref py py-class docutils literal notranslate"><span class="pre">decomposition.SparsePCA</span></code></a>
and <a class="reference internal" href="../modules/generated/sklearn.decomposition.MiniBatchSparsePCA.html#sklearn.decomposition.MiniBatchSparsePCA" title="sklearn.decomposition.MiniBatchSparsePCA"><code class="xref py py-class docutils literal notranslate"><span class="pre">decomposition.MiniBatchSparsePCA</span></code></a> to be convex and match the referenced
article. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/19210">#19210</a> by <a class="reference external" href="https://github.com/jeremiedbb">Jérémie du Boisberranger</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> <a class="reference internal" href="../modules/generated/sklearn.ensemble.RandomForestClassifier.html#sklearn.ensemble.RandomForestClassifier" title="sklearn.ensemble.RandomForestClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.RandomForestClassifier</span></code></a>,
<a class="reference internal" href="../modules/generated/sklearn.ensemble.RandomForestRegressor.html#sklearn.ensemble.RandomForestRegressor" title="sklearn.ensemble.RandomForestRegressor"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.RandomForestRegressor</span></code></a>,
<a class="reference internal" href="../modules/generated/sklearn.ensemble.ExtraTreesClassifier.html#sklearn.ensemble.ExtraTreesClassifier" title="sklearn.ensemble.ExtraTreesClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.ExtraTreesClassifier</span></code></a>, <a class="reference internal" href="../modules/generated/sklearn.ensemble.ExtraTreesRegressor.html#sklearn.ensemble.ExtraTreesRegressor" title="sklearn.ensemble.ExtraTreesRegressor"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.ExtraTreesRegressor</span></code></a>,
and <a class="reference internal" href="../modules/generated/sklearn.ensemble.RandomTreesEmbedding.html#sklearn.ensemble.RandomTreesEmbedding" title="sklearn.ensemble.RandomTreesEmbedding"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.RandomTreesEmbedding</span></code></a> now raise a <code class="docutils literal notranslate"><span class="pre">ValueError</span></code> when
<code class="docutils literal notranslate"><span class="pre">bootstrap=False</span></code> and <code class="docutils literal notranslate"><span class="pre">max_samples</span></code> is not <code class="docutils literal notranslate"><span class="pre">None</span></code>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21295">#21295</a> <a class="reference external" href="https://github.com/PSSF23">Haoyin Xu</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Solve a bug in <a class="reference internal" href="../modules/generated/sklearn.ensemble.GradientBoostingClassifier.html#sklearn.ensemble.GradientBoostingClassifier" title="sklearn.ensemble.GradientBoostingClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.GradientBoostingClassifier</span></code></a> where the
exponential loss was computing the positive gradient instead of the
negative one.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/22050">#22050</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> Fixed <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> by improving support
for base estimators that do not set <code class="docutils literal notranslate"><span class="pre">feature_names_in_</span></code>. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21991">#21991</a> by
<a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</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> Fix a bug in <a class="reference internal" href="../modules/generated/sklearn.linear_model.RidgeClassifierCV.html#sklearn.linear_model.RidgeClassifierCV" title="sklearn.linear_model.RidgeClassifierCV"><code class="xref py py-class docutils literal notranslate"><span class="pre">linear_model.RidgeClassifierCV</span></code></a> where the method
<code class="docutils literal notranslate"><span class="pre">predict</span></code> was performing an <code class="docutils literal notranslate"><span class="pre">argmax</span></code> on the scores obtained from
<code class="docutils literal notranslate"><span class="pre">decision_function</span></code> instead of returning the multilabel indicator matrix.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/19869">#19869</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>.</p></li>
</ul>
</section>
<section id="sklearn-linear-model">
<h4><a class="reference internal" href="../api/sklearn.linear_model.html#module-sklearn.linear_model" title="sklearn.linear_model"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.linear_model</span></code></a><a class="headerlink" href="#sklearn-linear-model" 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.linear_model.LassoLarsIC.html#sklearn.linear_model.LassoLarsIC" title="sklearn.linear_model.LassoLarsIC"><code class="xref py py-class docutils literal notranslate"><span class="pre">linear_model.LassoLarsIC</span></code></a> now correctly computes AIC
and BIC. An error is now raised when <code class="docutils literal notranslate"><span class="pre">n_features</span> <span class="pre">></span> <span class="pre">n_samples</span></code> and
when the noise variance is not provided.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21481">#21481</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a> and
<a class="reference external" href="https://github.com/ababino">Andrés Babino</a>.</p></li>
</ul>
</section>
<section id="sklearn-manifold">
<h4><a class="reference internal" href="../api/sklearn.manifold.html#module-sklearn.manifold" title="sklearn.manifold"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.manifold</span></code></a><a class="headerlink" href="#sklearn-manifold" 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> Fixed an unnecessary error when fitting <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">manifold.Isomap</span></code></a> with a
precomputed dense distance matrix where the neighbors graph has multiple
disconnected components. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21915">#21915</a> by <a class="reference external" href="https://github.com/TomDLT">Tom Dupre la Tour</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> All <a class="reference internal" href="../modules/generated/sklearn.metrics.DistanceMetric.html#sklearn.metrics.DistanceMetric" title="sklearn.metrics.DistanceMetric"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.metrics.DistanceMetric</span></code></a> subclasses now correctly support
read-only buffer attributes.
This fixes a regression introduced in 1.0.0 with respect to 0.24.2.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21694">#21694</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> All <code class="docutils literal notranslate"><span class="pre">sklearn.metrics.MinkowskiDistance</span></code> now accepts a weight
parameter that makes it possible to write code that behaves consistently both
with scipy 1.8 and earlier versions. In turns this means that all
neighbors-based estimators (except those that use <code class="docutils literal notranslate"><span class="pre">algorithm="kd_tree"</span></code>) now
accept a weight parameter with <code class="docutils literal notranslate"><span class="pre">metric="minknowski"</span></code> to yield results that
are always consistent with <code class="docutils literal notranslate"><span class="pre">scipy.spatial.distance.cdist</span></code>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21741">#21741</a> by <a class="reference external" href="https://github.com/ogrisel">Olivier Grisel</a>.</p></li>
</ul>
</section>
<section id="sklearn-multiclass">
<h4><a class="reference internal" href="../api/sklearn.multiclass.html#module-sklearn.multiclass" title="sklearn.multiclass"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.multiclass</span></code></a><a class="headerlink" href="#sklearn-multiclass" 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.multiclass.OneVsRestClassifier.html#sklearn.multiclass.OneVsRestClassifier.predict_proba" title="sklearn.multiclass.OneVsRestClassifier.predict_proba"><code class="xref py py-meth docutils literal notranslate"><span class="pre">multiclass.OneVsRestClassifier.predict_proba</span></code></a> does not error when
fitted on constant integer targets. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21871">#21871</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</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.KDTree.html#sklearn.neighbors.KDTree" title="sklearn.neighbors.KDTree"><code class="xref py py-class docutils literal notranslate"><span class="pre">neighbors.KDTree</span></code></a> and <a class="reference internal" href="../modules/generated/sklearn.neighbors.BallTree.html#sklearn.neighbors.BallTree" title="sklearn.neighbors.BallTree"><code class="xref py py-class docutils literal notranslate"><span class="pre">neighbors.BallTree</span></code></a> correctly supports
read-only buffer attributes. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21845">#21845</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</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> Fixes compatibility bug with NumPy 1.22 in <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>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21517">#21517</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</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> Prevents <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> from drawing out of the boundary of
the figure. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21917">#21917</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> 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. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21552">#21552</a> by <a class="reference external" href="https://github.com/lesteve">Loïc Estève</a>.</p></li>
</ul>
</section>
<section id="sklearn-utils">
<h4><a class="reference internal" href="../api/sklearn.utils.html#module-sklearn.utils" title="sklearn.utils"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.utils</span></code></a><a class="headerlink" href="#sklearn-utils" 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.utils.estimator_html_repr.html#sklearn.utils.estimator_html_repr" title="sklearn.utils.estimator_html_repr"><code class="xref py py-func docutils literal notranslate"><span class="pre">utils.estimator_html_repr</span></code></a> now escapes all the estimator
descriptions in the generated HTML. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21493">#21493</a> by
<a class="reference external" href="https://github.com/ageron">Aurélien Geron</a>.</p></li>
</ul>
</section>
</section>
</section>
<section id="version-1-0-1">
<span id="changes-1-0-1"></span><h2>Version 1.0.1<a class="headerlink" href="#version-1-0-1" title="Link to this heading">#</a></h2>
<p><strong>October 2021</strong></p>
<section id="fixed-models">
<h3>Fixed models<a class="headerlink" href="#fixed-models" 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> Non-fit methods in the following classes do not raise a UserWarning
when fitted on DataFrames with valid feature names:
<a class="reference internal" href="../modules/generated/sklearn.covariance.EllipticEnvelope.html#sklearn.covariance.EllipticEnvelope" title="sklearn.covariance.EllipticEnvelope"><code class="xref py py-class docutils literal notranslate"><span class="pre">covariance.EllipticEnvelope</span></code></a>, <a class="reference internal" href="../modules/generated/sklearn.ensemble.IsolationForest.html#sklearn.ensemble.IsolationForest" title="sklearn.ensemble.IsolationForest"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.IsolationForest</span></code></a>,
<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>, <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">neighbors.KNeighborsClassifier</span></code></a>,
<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">neighbors.KNeighborsRegressor</span></code></a>,
<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">neighbors.RadiusNeighborsClassifier</span></code></a>,
<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">neighbors.RadiusNeighborsRegressor</span></code></a>. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21199">#21199</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
</ul>
<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> Fixed <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> to take into account
<code class="docutils literal notranslate"><span class="pre">sample_weight</span></code> when computing the base estimator prediction when
<code class="docutils literal notranslate"><span class="pre">ensemble=False</span></code>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/20638">#20638</a> by <a class="reference external" href="https://github.com/JulienB-78">Julien Bohné</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Fixed a bug in <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> with
<code class="docutils literal notranslate"><span class="pre">method="sigmoid"</span></code> that was ignoring the <code class="docutils literal notranslate"><span class="pre">sample_weight</span></code> when computing the
the Bayesian priors.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21179">#21179</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>.</p></li>
</ul>
</section>
<section id="id1">
<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="#id1" 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> Fixed a bug in <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>, ensuring reproducibility and equivalence
between sparse and dense input. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21195">#21195</a>
by <a class="reference external" href="https://github.com/jeremiedbb">Jérémie du Boisberranger</a>.</p></li>
</ul>
</section>
<section id="id2">
<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="#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> Fixed a bug that could produce a segfault in rare cases for
<a class="reference internal" href="../modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html#sklearn.ensemble.HistGradientBoostingClassifier" title="sklearn.ensemble.HistGradientBoostingClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.HistGradientBoostingClassifier</span></code></a> and
<a class="reference internal" href="../modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html#sklearn.ensemble.HistGradientBoostingRegressor" title="sklearn.ensemble.HistGradientBoostingRegressor"><code class="xref py py-class docutils literal notranslate"><span class="pre">ensemble.HistGradientBoostingRegressor</span></code></a>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21130">#21130</a> <a class="reference external" href="https://github.com/lorentzenchr">Christian Lorentzen</a>.</p></li>
</ul>
</section>
<section id="sklearn-gaussian-process">
<h4><a class="reference internal" href="../api/sklearn.gaussian_process.html#module-sklearn.gaussian_process" title="sklearn.gaussian_process"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.gaussian_process</span></code></a><a class="headerlink" href="#sklearn-gaussian-process" 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> Compute <code class="docutils literal notranslate"><span class="pre">y_std</span></code> properly with multi-target in
<a class="reference internal" href="../modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html#sklearn.gaussian_process.GaussianProcessRegressor" title="sklearn.gaussian_process.GaussianProcessRegressor"><code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.gaussian_process.GaussianProcessRegressor</span></code></a> allowing
proper normalization in multi-target scene.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/20761">#20761</a> by <a class="reference external" href="https://github.com/patrickctrf">Patrick de C. T. R. Ferreira</a>.</p></li>
</ul>
</section>
<section id="sklearn-feature-extraction">
<h4><a class="reference internal" href="../api/sklearn.feature_extraction.html#module-sklearn.feature_extraction" title="sklearn.feature_extraction"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.feature_extraction</span></code></a><a class="headerlink" href="#sklearn-feature-extraction" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-info">Efficiency</span></span> Fixed an efficiency regression introduced in version 1.0.0 in the
<code class="docutils literal notranslate"><span class="pre">transform</span></code> method of <a class="reference internal" href="../modules/generated/sklearn.feature_extraction.text.CountVectorizer.html#sklearn.feature_extraction.text.CountVectorizer" title="sklearn.feature_extraction.text.CountVectorizer"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_extraction.text.CountVectorizer</span></code></a> which no
longer checks for uppercase characters in the provided vocabulary. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21251">#21251</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> Fixed a bug in <a class="reference internal" href="../modules/generated/sklearn.feature_extraction.text.CountVectorizer.html#sklearn.feature_extraction.text.CountVectorizer" title="sklearn.feature_extraction.text.CountVectorizer"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_extraction.text.CountVectorizer</span></code></a> and
<a class="reference internal" href="../modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html#sklearn.feature_extraction.text.TfidfVectorizer" title="sklearn.feature_extraction.text.TfidfVectorizer"><code class="xref py py-class docutils literal notranslate"><span class="pre">feature_extraction.text.TfidfVectorizer</span></code></a> by raising an
error when ‘min_idf’ or ‘max_idf’ are floating-point numbers greater than 1.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/20752">#20752</a> by <a class="reference external" href="https://github.com/AlekLefebvre">Alek Lefebvre</a>.</p></li>
</ul>
</section>
<section id="id3">
<h4><a class="reference internal" href="../api/sklearn.linear_model.html#module-sklearn.linear_model" title="sklearn.linear_model"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.linear_model</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> Improves stability of <a class="reference internal" href="../modules/generated/sklearn.linear_model.LassoLars.html#sklearn.linear_model.LassoLars" title="sklearn.linear_model.LassoLars"><code class="xref py py-class docutils literal notranslate"><span class="pre">linear_model.LassoLars</span></code></a> for different
versions of openblas. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21340">#21340</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.linear_model.LogisticRegression.html#sklearn.linear_model.LogisticRegression" title="sklearn.linear_model.LogisticRegression"><code class="xref py py-class docutils literal notranslate"><span class="pre">linear_model.LogisticRegression</span></code></a> now raises a better error
message when the solver does not support sparse matrices with int64 indices.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21093">#21093</a> by <a class="reference external" href="https://github.com/TomDLT">Tom Dupre la Tour</a>.</p></li>
</ul>
</section>
<section id="id4">
<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="#id4" 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" title="sklearn.neighbors.KNeighborsClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">neighbors.KNeighborsClassifier</span></code></a>,
<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">neighbors.KNeighborsRegressor</span></code></a>,
<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">neighbors.RadiusNeighborsClassifier</span></code></a>,
<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">neighbors.RadiusNeighborsRegressor</span></code></a> with <code class="docutils literal notranslate"><span class="pre">metric="precomputed"</span></code> raises
an error for <code class="docutils literal notranslate"><span class="pre">bsr</span></code> and <code class="docutils literal notranslate"><span class="pre">dok</span></code> sparse matrices in methods: <code class="docutils literal notranslate"><span class="pre">fit</span></code>, <code class="docutils literal notranslate"><span class="pre">kneighbors</span></code>
and <code class="docutils literal notranslate"><span class="pre">radius_neighbors</span></code>, due to handling of explicit zeros in <code class="docutils literal notranslate"><span class="pre">bsr</span></code> and <code class="docutils literal notranslate"><span class="pre">dok</span></code>
<a class="reference internal" href="../glossary.html#term-sparse-graph"><span class="xref std std-term">sparse graph</span></a> formats. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21199">#21199</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
</ul>
</section>
<section id="sklearn-pipeline">
<h4><a class="reference internal" href="../api/sklearn.pipeline.html#module-sklearn.pipeline" title="sklearn.pipeline"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.pipeline</span></code></a><a class="headerlink" href="#sklearn-pipeline" 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.pipeline.Pipeline.html#sklearn.pipeline.Pipeline.get_feature_names_out" title="sklearn.pipeline.Pipeline.get_feature_names_out"><code class="xref py py-meth docutils literal notranslate"><span class="pre">pipeline.Pipeline.get_feature_names_out</span></code></a> correctly passes feature
names out from one step of a pipeline to the next. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21351">#21351</a> by
<a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
</ul>
</section>
<section id="sklearn-svm">
<h4><a class="reference internal" href="../api/sklearn.svm.html#module-sklearn.svm" title="sklearn.svm"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.svm</span></code></a><a class="headerlink" href="#sklearn-svm" 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.svm.SVC.html#sklearn.svm.SVC" title="sklearn.svm.SVC"><code class="xref py py-class docutils literal notranslate"><span class="pre">svm.SVC</span></code></a> and <a class="reference internal" href="../modules/generated/sklearn.svm.SVR.html#sklearn.svm.SVR" title="sklearn.svm.SVR"><code class="xref py py-class docutils literal notranslate"><span class="pre">svm.SVR</span></code></a> check for an inconsistency
in its internal representation and raise an error instead of segfaulting.
This fix also resolves
<a class="reference external" href="https://nvd.nist.gov/vuln/detail/CVE-2020-28975">CVE-2020-28975</a>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21336">#21336</a> by <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>.</p></li>
</ul>
</section>
<section id="id5">
<h4><a class="reference internal" href="../api/sklearn.utils.html#module-sklearn.utils" title="sklearn.utils"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.utils</span></code></a><a class="headerlink" href="#id5" title="Link to this heading">#</a></h4>
<ul class="simple">
<li><p><span class="raw-html"><span class="badge text-bg-info">Enhancement</span></span> <code class="docutils literal notranslate"><span class="pre">utils.validation._check_sample_weight</span></code> can perform a
non-negativity check on the sample weights. It can be turned on
using the only_non_negative bool parameter.
Estimators that check for non-negative weights are updated:
<a class="reference internal" href="../modules/generated/sklearn.linear_model.LinearRegression.html#sklearn.linear_model.LinearRegression" title="sklearn.linear_model.LinearRegression"><code class="xref py py-func docutils literal notranslate"><span class="pre">linear_model.LinearRegression</span></code></a> (here the previous
error message was misleading),
<a class="reference internal" href="../modules/generated/sklearn.ensemble.AdaBoostClassifier.html#sklearn.ensemble.AdaBoostClassifier" title="sklearn.ensemble.AdaBoostClassifier"><code class="xref py py-func docutils literal notranslate"><span class="pre">ensemble.AdaBoostClassifier</span></code></a>,
<a class="reference internal" href="../modules/generated/sklearn.ensemble.AdaBoostRegressor.html#sklearn.ensemble.AdaBoostRegressor" title="sklearn.ensemble.AdaBoostRegressor"><code class="xref py py-func docutils literal notranslate"><span class="pre">ensemble.AdaBoostRegressor</span></code></a>,
<a class="reference internal" href="../modules/generated/sklearn.neighbors.KernelDensity.html#sklearn.neighbors.KernelDensity" title="sklearn.neighbors.KernelDensity"><code class="xref py py-func docutils literal notranslate"><span class="pre">neighbors.KernelDensity</span></code></a>.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/20880">#20880</a> by <a class="reference external" href="https://github.com/glemaitre">Guillaume Lemaitre</a>
and <a class="reference external" href="https://github.com/simonandras">András Simon</a>.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> Solve a bug in <code class="docutils literal notranslate"><span class="pre">sklearn.utils.metaestimators.if_delegate_has_method</span></code>
where the underlying check for an attribute did not work with NumPy arrays.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21145">#21145</a> by <a class="reference external" href="https://github.com/Zahlii">Zahlii</a>.</p></li>
</ul>
</section>
<section id="miscellaneous">
<h4>Miscellaneous<a class="headerlink" href="#miscellaneous" 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> Fitting an estimator on a dataset that has no feature names, that was previously
fitted on a dataset with feature names no longer keeps the old feature names stored in
the <code class="docutils literal notranslate"><span class="pre">feature_names_in_</span></code> attribute. <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/21389">#21389</a> by
<a class="reference external" href="https://github.com/jeremiedbb">Jérémie du Boisberranger</a>.</p></li>
</ul>
</section>
</section>
</section>
<section id="version-1-0-0">
<span id="changes-1-0"></span><h2>Version 1.0.0<a class="headerlink" href="#version-1-0-0" title="Link to this heading">#</a></h2>
<p><strong>September 2021</strong></p>
<section id="minimal-dependencies">
<h3>Minimal dependencies<a class="headerlink" href="#minimal-dependencies" title="Link to this heading">#</a></h3>
<p>Version 1.0.0 of scikit-learn requires python 3.7+, numpy 1.14.6+ and
scipy 1.1.0+. Optional minimal dependency is matplotlib 2.2.2+.</p>
</section>
<section id="enforcing-keyword-only-arguments">
<h3>Enforcing keyword-only arguments<a class="headerlink" href="#enforcing-keyword-only-arguments" title="Link to this heading">#</a></h3>
<p>In an effort to promote clear and non-ambiguous use of the library, most
constructor and function parameters must now be passed as keyword arguments
(i.e. using the <code class="docutils literal notranslate"><span class="pre">param=value</span></code> syntax) instead of positional. If a keyword-only
parameter is used as positional, a <code class="docutils literal notranslate"><span class="pre">TypeError</span></code> is now raised.
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues/15005">#15005</a> <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pull/20002">#20002</a> by <a class="reference external" href="https://joelnothman.com/">Joel Nothman</a>, <a class="reference external" href="https://github.com/adrinjalali">Adrin Jalali</a>, <a class="reference external" href="https://github.com/thomasjpfan">Thomas Fan</a>,
<a class="reference external" href="https://github.com/NicolasHug">Nicolas Hug</a>, and <a class="reference external" href="https://github.com/TomDLT">Tom Dupre la Tour</a>. See <a class="reference external" href="https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep009/proposal.html">SLEP009</a>
for more details.</p>
</section>
<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> <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">manifold.TSNE</span></code></a> now avoids numerical underflow issues during
affinity matrix computation.</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.manifold.Isomap.html#sklearn.manifold.Isomap" title="sklearn.manifold.Isomap"><code class="xref py py-class docutils literal notranslate"><span class="pre">manifold.Isomap</span></code></a> now connects disconnected components of the
neighbors graph along some minimum distance pairs, instead of changing
every infinite distances to zero.</p></li>
<li><p><span class="raw-html"><span class="badge text-bg-danger">Fix</span></span> The splitting criterion of <a class="reference internal" href="../modules/generated/sklearn.tree.DecisionTreeClassifier.html#sklearn.tree.DecisionTreeClassifier" title="sklearn.tree.DecisionTreeClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">tree.DecisionTreeClassifier</span></code></a> and
<a class="reference internal" href="../modules/generated/sklearn.tree.DecisionTreeRegressor.html#sklearn.tree.DecisionTreeRegressor" title="sklearn.tree.DecisionTreeRegressor"><code class="xref py py-class docutils literal notranslate"><span class="pre">tree.DecisionTreeRegressor</span></code></a> can be impacted by a fix in the handling
of rounding errors. Previously some extra spurious splits could occur.</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.train_test_split.html#sklearn.model_selection.train_test_split" title="sklearn.model_selection.train_test_split"><code class="xref py py-func docutils literal notranslate"><span class="pre">model_selection.train_test_split</span></code></a> with a <code class="docutils literal notranslate"><span class="pre">stratify</span></code> parameter
and <a class="reference internal" href="../modules/generated/sklearn.model_selection.StratifiedShuffleSplit.html#sklearn.model_selection.StratifiedShuffleSplit" title="sklearn.model_selection.StratifiedShuffleSplit"><code class="xref py py-class docutils literal notranslate"><span class="pre">model_selection.StratifiedShuffleSplit</span></code></a> may lead to slightly
different results.</p></li>
</ul>
<p>Details are listed in the changelog below.</p>
<p>(While we are trying to better inform users by providing this information, we
cannot assure that this list is complete.)</p>
</section>
<section id="id6">