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<section id="installing-scikit-learn">
<span id="installation-instructions"></span><h1>Installing scikit-learn<a class="headerlink" href="#installing-scikit-learn" title="Link to this heading">#</a></h1>
<p>There are different ways to install scikit-learn:</p>
<ul class="simple">
<li><p><a class="reference internal" href="#install-official-release"><span class="std std-ref">Install the latest official release</span></a>. This
is the best approach for most users. It will provide a stable version
and pre-built packages are available for most platforms.</p></li>
<li><p>Install the version of scikit-learn provided by your
<a class="reference internal" href="#install-by-distribution"><span class="std std-ref">operating system or Python distribution</span></a>.
This is a quick option for those who have operating systems or Python
distributions that distribute scikit-learn.
It might not provide the latest release version.</p></li>
<li><p><a class="reference internal" href="developers/advanced_installation.html#install-bleeding-edge"><span class="std std-ref">Building the package from source</span></a>. This is best for users who want the
latest-and-greatest features and aren’t afraid of running
brand-new code. This is also needed for users who wish to contribute to the
project.</p></li>
</ul>
<section id="installing-the-latest-release">
<span id="install-official-release"></span><h2>Installing the latest release<a class="headerlink" href="#installing-the-latest-release" title="Link to this heading">#</a></h2>
<style>
/* Show caption on large screens */
@media screen and (min-width: 960px) {
.install-instructions .sd-tab-set {
--tab-caption-width: 20%;
}
.install-instructions .sd-tab-set.tabs-os::before {
content: "Operating System";
}
.install-instructions .sd-tab-set.tabs-package-manager::before {
content: "Package Manager";
}
}
</style><div class="install-instructions docutils">
<div class="sd-tab-set tabs-os docutils">
<input checked="checked" id="sd-tab-item-0" name="sd-tab-set-0" type="radio">
<label class="sd-tab-label tab-4" for="sd-tab-item-0">
Windows</label><div class="sd-tab-content docutils">
<div class="sd-tab-set tabs-package-manager docutils">
<input checked="checked" id="sd-tab-item-3" name="sd-tab-set-1" type="radio">
<label class="sd-tab-label tab-6" data-sync-group="tab" data-sync-id="package-manager-pip" for="sd-tab-item-3">
pip</label><div class="sd-tab-content docutils">
<p>Install the 64-bit version of Python 3, for instance from the
<a class="reference external" href="https://www.python.org/downloads/windows/">official website</a>.</p>
<p>Now create a <a class="reference external" href="https://docs.python.org/3/tutorial/venv.html">virtual environment (venv)</a> and install scikit-learn.
Note that the virtual environment is optional but strongly recommended, in
order to avoid potential conflicts with other packages.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><style type="text/css">
span.prompt1:before {
content: "PS C:\\> ";
}
</style><span class="prompt1"><span class="n">python</span> <span class="n">-m</span> <span class="n">venv</span> <span class="n">sklearn-env</span></span>
<span class="prompt1"><span class="n">sklearn-env</span><span class="p">\</span><span class="n">Scripts</span><span class="p">\</span><span class="n">activate</span> <span class="c"># activate</span></span>
<span class="prompt1"><span class="n">pip</span> <span class="n">install</span> <span class="n">-U</span> <span class="n">scikit-learn</span></span>
</pre></div></div><p>In order to check your installation, you can use:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1"><span class="n">python</span> <span class="n">-m</span> <span class="n">pip</span> <span class="n">show</span> <span class="n">scikit-learn</span> <span class="c"># show scikit-learn version and location</span></span>
<span class="prompt1"><span class="n">python</span> <span class="n">-m</span> <span class="n">pip</span> <span class="n">freeze</span> <span class="c"># show all installed packages in the environment</span></span>
<span class="prompt1"><span class="n">python</span> <span class="n">-c</span> <span class="s2">"import sklearn; sklearn.show_versions()"</span></span>
</pre></div></div></div>
<input id="sd-tab-item-4" name="sd-tab-set-1" type="radio">
<label class="sd-tab-label tab-6" data-sync-group="tab" data-sync-id="package-manager-conda" for="sd-tab-item-4">
conda</label><div class="sd-tab-content docutils">
<p>Install conda using the
<a class="reference external" href="https://conda-forge.org/download/">conda-forge installers</a> (no
administrator permission required). Then run:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><style type="text/css">
span.prompt2:before {
content: "$ ";
}
</style><span class="prompt2">conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>sklearn-env<span class="w"> </span>-c<span class="w"> </span>conda-forge<span class="w"> </span>scikit-learn</span>
<span class="prompt2">conda<span class="w"> </span>activate<span class="w"> </span>sklearn-env</span>
</pre></div></div><p>In order to check your installation, you can use:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">conda<span class="w"> </span>list<span class="w"> </span>scikit-learn<span class="w"> </span><span class="c1"># show scikit-learn version and location</span></span>
<span class="prompt2">conda<span class="w"> </span>list<span class="w"> </span><span class="c1"># show all installed packages in the environment</span></span>
<span class="prompt2">python<span class="w"> </span>-c<span class="w"> </span><span class="s2">"import sklearn; sklearn.show_versions()"</span></span>
</pre></div></div></div>
</div>
</div>
<input id="sd-tab-item-1" name="sd-tab-set-0" type="radio">
<label class="sd-tab-label tab-4" for="sd-tab-item-1">
MacOS</label><div class="sd-tab-content docutils">
<div class="sd-tab-set tabs-package-manager docutils">
<input checked="checked" id="sd-tab-item-5" name="sd-tab-set-2" type="radio">
<label class="sd-tab-label tab-6" data-sync-group="tab" data-sync-id="package-manager-pip" for="sd-tab-item-5">
pip</label><div class="sd-tab-content docutils">
<p>Install Python 3 using <a class="reference external" href="https://brew.sh/">homebrew</a> (<code class="docutils literal notranslate"><span class="pre">brew</span> <span class="pre">install</span> <span class="pre">python</span></code>)
or by manually installing the package from the <a class="reference external" href="https://www.python.org/downloads/macos/">official website</a>.</p>
<p>Now create a <a class="reference external" href="https://docs.python.org/3/tutorial/venv.html">virtual environment (venv)</a> and install scikit-learn.
Note that the virtual environment is optional but strongly recommended, in
order to avoid potential conflicts with other packges.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">python<span class="w"> </span>-m<span class="w"> </span>venv<span class="w"> </span>sklearn-env</span>
<span class="prompt2"><span class="nb">source</span><span class="w"> </span>sklearn-env/bin/activate<span class="w"> </span><span class="c1"># activate</span></span>
<span class="prompt2">pip<span class="w"> </span>install<span class="w"> </span>-U<span class="w"> </span>scikit-learn</span>
</pre></div></div><p>In order to check your installation, you can use:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">python<span class="w"> </span>-m<span class="w"> </span>pip<span class="w"> </span>show<span class="w"> </span>scikit-learn<span class="w"> </span><span class="c1"># show scikit-learn version and location</span></span>
<span class="prompt2">python<span class="w"> </span>-m<span class="w"> </span>pip<span class="w"> </span>freeze<span class="w"> </span><span class="c1"># show all installed packages in the environment</span></span>
<span class="prompt2">python<span class="w"> </span>-c<span class="w"> </span><span class="s2">"import sklearn; sklearn.show_versions()"</span></span>
</pre></div></div></div>
<input id="sd-tab-item-6" name="sd-tab-set-2" type="radio">
<label class="sd-tab-label tab-6" data-sync-group="tab" data-sync-id="package-manager-conda" for="sd-tab-item-6">
conda</label><div class="sd-tab-content docutils">
<p>Install conda using the
<a class="reference external" href="https://conda-forge.org/download/">conda-forge installers</a> (no
administrator permission required). Then run:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>sklearn-env<span class="w"> </span>-c<span class="w"> </span>conda-forge<span class="w"> </span>scikit-learn</span>
<span class="prompt2">conda<span class="w"> </span>activate<span class="w"> </span>sklearn-env</span>
</pre></div></div><p>In order to check your installation, you can use:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">conda<span class="w"> </span>list<span class="w"> </span>scikit-learn<span class="w"> </span><span class="c1"># show scikit-learn version and location</span></span>
<span class="prompt2">conda<span class="w"> </span>list<span class="w"> </span><span class="c1"># show all installed packages in the environment</span></span>
<span class="prompt2">python<span class="w"> </span>-c<span class="w"> </span><span class="s2">"import sklearn; sklearn.show_versions()"</span></span>
</pre></div></div></div>
</div>
</div>
<input id="sd-tab-item-2" name="sd-tab-set-0" type="radio">
<label class="sd-tab-label tab-4" for="sd-tab-item-2">
Linux</label><div class="sd-tab-content docutils">
<div class="sd-tab-set tabs-package-manager docutils">
<input checked="checked" id="sd-tab-item-7" name="sd-tab-set-3" type="radio">
<label class="sd-tab-label tab-6" data-sync-group="tab" data-sync-id="package-manager-pip" for="sd-tab-item-7">
pip</label><div class="sd-tab-content docutils">
<p>Python 3 is usually installed by default on most Linux distributions. To
check if you have it installed, try:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">python3<span class="w"> </span>--version</span>
<span class="prompt2">pip3<span class="w"> </span>--version</span>
</pre></div></div><p>If you don’t have Python 3 installed, please install <code class="docutils literal notranslate"><span class="pre">python3</span></code> and
<code class="docutils literal notranslate"><span class="pre">python3-pip</span></code> from your distribution’s package manager.</p>
<p>Now create a <a class="reference external" href="https://docs.python.org/3/tutorial/venv.html">virtual environment (venv)</a> and install scikit-learn.
Note that the virtual environment is optional but strongly recommended, in
order to avoid potential conflicts with other packages.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">python3<span class="w"> </span>-m<span class="w"> </span>venv<span class="w"> </span>sklearn-env</span>
<span class="prompt2"><span class="nb">source</span><span class="w"> </span>sklearn-env/bin/activate<span class="w"> </span><span class="c1"># activate</span></span>
<span class="prompt2">pip3<span class="w"> </span>install<span class="w"> </span>-U<span class="w"> </span>scikit-learn</span>
</pre></div></div><p>In order to check your installation, you can use:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">python3<span class="w"> </span>-m<span class="w"> </span>pip<span class="w"> </span>show<span class="w"> </span>scikit-learn<span class="w"> </span><span class="c1"># show scikit-learn version and location</span></span>
<span class="prompt2">python3<span class="w"> </span>-m<span class="w"> </span>pip<span class="w"> </span>freeze<span class="w"> </span><span class="c1"># show all installed packages in the environment</span></span>
<span class="prompt2">python3<span class="w"> </span>-c<span class="w"> </span><span class="s2">"import sklearn; sklearn.show_versions()"</span></span>
</pre></div></div></div>
<input id="sd-tab-item-8" name="sd-tab-set-3" type="radio">
<label class="sd-tab-label tab-6" data-sync-group="tab" data-sync-id="package-manager-conda" for="sd-tab-item-8">
conda</label><div class="sd-tab-content docutils">
<p>Install conda using the
<a class="reference external" href="https://conda-forge.org/download/">conda-forge installers</a> (no
administrator permission required). Then run:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>sklearn-env<span class="w"> </span>-c<span class="w"> </span>conda-forge<span class="w"> </span>scikit-learn</span>
<span class="prompt2">conda<span class="w"> </span>activate<span class="w"> </span>sklearn-env</span>
</pre></div></div><p>In order to check your installation, you can use:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">conda<span class="w"> </span>list<span class="w"> </span>scikit-learn<span class="w"> </span><span class="c1"># show scikit-learn version and location</span></span>
<span class="prompt2">conda<span class="w"> </span>list<span class="w"> </span><span class="c1"># show all installed packages in the environment</span></span>
<span class="prompt2">python<span class="w"> </span>-c<span class="w"> </span><span class="s2">"import sklearn; sklearn.show_versions()"</span></span>
</pre></div></div></div>
</div>
</div>
</div>
</div>
<p>Using an isolated environment such as pip venv or conda makes it possible to
install a specific version of scikit-learn with pip or conda and its dependencies
independently of any previously installed Python packages. In particular under Linux
it is discouraged to install pip packages alongside the packages managed by the
package manager of the distribution (apt, dnf, pacman…).</p>
<p>Note that you should always remember to activate the environment of your choice
prior to running any Python command whenever you start a new terminal session.</p>
<p>If you have not installed NumPy or SciPy yet, you can also install these using
conda or pip. When using pip, please ensure that <em>binary wheels</em> are used,
and NumPy and SciPy are not recompiled from source, which can happen when using
particular configurations of operating system and hardware (such as Linux on
a Raspberry Pi).</p>
<p>Scikit-learn plotting capabilities (i.e., functions starting with <code class="docutils literal notranslate"><span class="pre">plot_</span></code>
and classes ending with <code class="docutils literal notranslate"><span class="pre">Display</span></code>) require Matplotlib. The examples require
Matplotlib and some examples require scikit-image, pandas, or seaborn. The
minimum version of scikit-learn dependencies are listed below along with its
purpose.</p>
<div class="pst-scrollable-table-container"><table class="table">
<thead>
<tr class="row-odd"><th class="head"><p>Dependency</p></th>
<th class="head"><p>Minimum Version</p></th>
<th class="head"><p>Purpose</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p>numpy</p></td>
<td><p>1.19.5</p></td>
<td><p>build, install</p></td>
</tr>
<tr class="row-odd"><td><p>scipy</p></td>
<td><p>1.6.0</p></td>
<td><p>build, install</p></td>
</tr>
<tr class="row-even"><td><p>joblib</p></td>
<td><p>1.2.0</p></td>
<td><p>install</p></td>
</tr>
<tr class="row-odd"><td><p>threadpoolctl</p></td>
<td><p>3.1.0</p></td>
<td><p>install</p></td>
</tr>
<tr class="row-even"><td><p>cython</p></td>
<td><p>3.0.10</p></td>
<td><p>build</p></td>
</tr>
<tr class="row-odd"><td><p>meson-python</p></td>
<td><p>0.16.0</p></td>
<td><p>build</p></td>
</tr>
<tr class="row-even"><td><p>matplotlib</p></td>
<td><p>3.3.4</p></td>
<td><p>benchmark, docs, examples, tests</p></td>
</tr>
<tr class="row-odd"><td><p>scikit-image</p></td>
<td><p>0.17.2</p></td>
<td><p>docs, examples, tests</p></td>
</tr>
<tr class="row-even"><td><p>pandas</p></td>
<td><p>1.1.5</p></td>
<td><p>benchmark, docs, examples, tests</p></td>
</tr>
<tr class="row-odd"><td><p>seaborn</p></td>
<td><p>0.9.0</p></td>
<td><p>docs, examples</p></td>
</tr>
<tr class="row-even"><td><p>memory_profiler</p></td>
<td><p>0.57.0</p></td>
<td><p>benchmark, docs</p></td>
</tr>
<tr class="row-odd"><td><p>pytest</p></td>
<td><p>7.1.2</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-even"><td><p>pytest-cov</p></td>
<td><p>2.9.0</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-odd"><td><p>ruff</p></td>
<td><p>0.5.1</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-even"><td><p>black</p></td>
<td><p>24.3.0</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-odd"><td><p>mypy</p></td>
<td><p>1.9</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-even"><td><p>pyamg</p></td>
<td><p>4.0.0</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-odd"><td><p>polars</p></td>
<td><p>0.20.30</p></td>
<td><p>docs, tests</p></td>
</tr>
<tr class="row-even"><td><p>pyarrow</p></td>
<td><p>12.0.0</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-odd"><td><p>sphinx</p></td>
<td><p>7.3.7</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-even"><td><p>sphinx-copybutton</p></td>
<td><p>0.5.2</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-odd"><td><p>sphinx-gallery</p></td>
<td><p>0.17.1</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-even"><td><p>numpydoc</p></td>
<td><p>1.2.0</p></td>
<td><p>docs, tests</p></td>
</tr>
<tr class="row-odd"><td><p>Pillow</p></td>
<td><p>7.1.2</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-even"><td><p>pooch</p></td>
<td><p>1.6.0</p></td>
<td><p>docs, examples, tests</p></td>
</tr>
<tr class="row-odd"><td><p>sphinx-prompt</p></td>
<td><p>1.4.0</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-even"><td><p>sphinxext-opengraph</p></td>
<td><p>0.9.1</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-odd"><td><p>plotly</p></td>
<td><p>5.14.0</p></td>
<td><p>docs, examples</p></td>
</tr>
<tr class="row-even"><td><p>sphinxcontrib-sass</p></td>
<td><p>0.3.4</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-odd"><td><p>sphinx-remove-toctrees</p></td>
<td><p>1.0.0.post1</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-even"><td><p>sphinx-design</p></td>
<td><p>0.6.0</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-odd"><td><p>pydata-sphinx-theme</p></td>
<td><p>0.15.3</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-even"><td><p>towncrier</p></td>
<td><p>24.8.0</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-odd"><td><p>conda-lock</p></td>
<td><p>2.5.6</p></td>
<td><p>maintenance</p></td>
</tr>
</tbody>
</table>
</div>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>Scikit-learn 0.20 was the last version to support Python 2.7 and Python 3.4.
Scikit-learn 0.21 supported Python 3.5-3.7.
Scikit-learn 0.22 supported Python 3.5-3.8.
Scikit-learn 0.23-0.24 required Python 3.6 or newer.
Scikit-learn 1.0 supported Python 3.7-3.10.
Scikit-learn 1.1, 1.2 and 1.3 support Python 3.8-3.12
Scikit-learn 1.4 requires Python 3.9 or newer.</p>
</div>
</section>
<section id="third-party-distributions-of-scikit-learn">
<span id="install-by-distribution"></span><h2>Third party distributions of scikit-learn<a class="headerlink" href="#third-party-distributions-of-scikit-learn" title="Link to this heading">#</a></h2>
<p>Some third-party distributions provide versions of
scikit-learn integrated with their package-management systems.</p>
<p>These can make installation and upgrading much easier for users since
the integration includes the ability to automatically install
dependencies (numpy, scipy) that scikit-learn requires.</p>
<p>The following is an incomplete list of OS and python distributions
that provide their own version of scikit-learn.</p>
<section id="alpine-linux">
<h3>Alpine Linux<a class="headerlink" href="#alpine-linux" title="Link to this heading">#</a></h3>
<p>Alpine Linux’s package is provided through the <a class="reference external" href="https://pkgs.alpinelinux.org/packages?name=py3-scikit-learn">official repositories</a> as
<code class="docutils literal notranslate"><span class="pre">py3-scikit-learn</span></code> for Python.
It can be installed by typing the following command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">sudo<span class="w"> </span>apk<span class="w"> </span>add<span class="w"> </span>py3-scikit-learn</span>
</pre></div></div></section>
<section id="arch-linux">
<h3>Arch Linux<a class="headerlink" href="#arch-linux" title="Link to this heading">#</a></h3>
<p>Arch Linux’s package is provided through the <a class="reference external" href="https://www.archlinux.org/packages/?q=scikit-learn">official repositories</a> as
<code class="docutils literal notranslate"><span class="pre">python-scikit-learn</span></code> for Python.
It can be installed by typing the following command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">sudo<span class="w"> </span>pacman<span class="w"> </span>-S<span class="w"> </span>python-scikit-learn</span>
</pre></div></div></section>
<section id="debian-ubuntu">
<h3>Debian/Ubuntu<a class="headerlink" href="#debian-ubuntu" title="Link to this heading">#</a></h3>
<p>The Debian/Ubuntu package is split in three different packages called
<code class="docutils literal notranslate"><span class="pre">python3-sklearn</span></code> (python modules), <code class="docutils literal notranslate"><span class="pre">python3-sklearn-lib</span></code> (low-level
implementations and bindings), <code class="docutils literal notranslate"><span class="pre">python-sklearn-doc</span></code> (documentation).
Note that scikit-learn requires Python 3, hence the need to use the <code class="docutils literal notranslate"><span class="pre">python3-</span></code>
suffixed package names.
Packages can be installed using <code class="docutils literal notranslate"><span class="pre">apt-get</span></code>:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">sudo<span class="w"> </span>apt-get<span class="w"> </span>install<span class="w"> </span>python3-sklearn<span class="w"> </span>python3-sklearn-lib<span class="w"> </span>python-sklearn-doc</span>
</pre></div></div></section>
<section id="fedora">
<h3>Fedora<a class="headerlink" href="#fedora" title="Link to this heading">#</a></h3>
<p>The Fedora package is called <code class="docutils literal notranslate"><span class="pre">python3-scikit-learn</span></code> for the python 3 version,
the only one available in Fedora.
It can be installed using <code class="docutils literal notranslate"><span class="pre">dnf</span></code>:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">sudo<span class="w"> </span>dnf<span class="w"> </span>install<span class="w"> </span>python3-scikit-learn</span>
</pre></div></div></section>
<section id="netbsd">
<h3>NetBSD<a class="headerlink" href="#netbsd" title="Link to this heading">#</a></h3>
<p>scikit-learn is available via <a class="reference external" href="http://pkgsrc-wip.sourceforge.net/">pkgsrc-wip</a>:
<a class="reference external" href="https://pkgsrc.se/math/py-scikit-learn">https://pkgsrc.se/math/py-scikit-learn</a></p>
</section>
<section id="macports-for-mac-osx">
<h3>MacPorts for Mac OSX<a class="headerlink" href="#macports-for-mac-osx" title="Link to this heading">#</a></h3>
<p>The MacPorts package is named <code class="docutils literal notranslate"><span class="pre">py<XY>-scikits-learn</span></code>,
where <code class="docutils literal notranslate"><span class="pre">XY</span></code> denotes the Python version.
It can be installed by typing the following
command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">sudo<span class="w"> </span>port<span class="w"> </span>install<span class="w"> </span>py39-scikit-learn</span>
</pre></div></div></section>
<section id="anaconda-and-enthought-deployment-manager-for-all-supported-platforms">
<h3>Anaconda and Enthought Deployment Manager for all supported platforms<a class="headerlink" href="#anaconda-and-enthought-deployment-manager-for-all-supported-platforms" title="Link to this heading">#</a></h3>
<p><a class="reference external" href="https://www.anaconda.com/download">Anaconda</a> and
<a class="reference external" href="https://assets.enthought.com/downloads/">Enthought Deployment Manager</a>
both ship with scikit-learn in addition to a large set of scientific
python library for Windows, Mac OSX and Linux.</p>
<p>Anaconda offers scikit-learn as part of its free distribution.</p>
</section>
<section id="intel-extension-for-scikit-learn">
<h3>Intel Extension for Scikit-learn<a class="headerlink" href="#intel-extension-for-scikit-learn" title="Link to this heading">#</a></h3>
<p>Intel maintains an optimized x86_64 package, available in PyPI (via <code class="docutils literal notranslate"><span class="pre">pip</span></code>),
and in the <code class="docutils literal notranslate"><span class="pre">main</span></code>, <code class="docutils literal notranslate"><span class="pre">conda-forge</span></code> and <code class="docutils literal notranslate"><span class="pre">intel</span></code> conda channels:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt2">conda<span class="w"> </span>install<span class="w"> </span>scikit-learn-intelex</span>
</pre></div></div><p>This package has an Intel optimized version of many estimators. Whenever
an alternative implementation doesn’t exist, scikit-learn implementation
is used as a fallback. Those optimized solvers come from the oneDAL
C++ library and are optimized for the x86_64 architecture, and are
optimized for multi-core Intel CPUs.</p>
<p>Note that those solvers are not enabled by default, please refer to the
<a class="reference external" href="https://intel.github.io/scikit-learn-intelex/latest/what-is-patching.html">scikit-learn-intelex</a>
documentation for more details on usage scenarios. Direct export example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><style type="text/css">
span.prompt3:before {