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<li><a class="reference internal" href="#">Installing scikit-learn</a><ul>
<li><a class="reference internal" href="#installing-the-latest-release">Installing the latest release</a></li>
<li><a class="reference internal" href="#installing-on-apple-silicon-m1-hardware">Installing on Apple Silicon M1 hardware</a></li>
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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="Permalink to this heading">¶</a></h1>
<p>There are different ways to install scikit-learn:</p>
<blockquote>
<div><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>
</div></blockquote>
<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="Permalink to this heading">¶</a></h2>
<div class="install">
<strong>Operating System</strong>
<input type="radio" name="os" id="quickstart-win" checked>
<label for="quickstart-win">Windows</label>
<input type="radio" name="os" id="quickstart-mac">
<label for="quickstart-mac">macOS</label>
<input type="radio" name="os" id="quickstart-lin">
<label for="quickstart-lin">Linux</label><br />
<strong>Packager</strong>
<input type="radio" name="packager" id="quickstart-pip" checked>
<label for="quickstart-pip">pip</label>
<input type="radio" name="packager" id="quickstart-conda">
<label for="quickstart-conda">conda</label><br />
<input type="checkbox" name="config" id="quickstart-venv">
<label for="quickstart-venv"></label>
</span><div>
<span class="sk-expandable" data-packager="pip" data-os="windows">Install the 64bit version of Python 3, for instance from <a href="https://www.python.org/">https://www.python.org</a>.</span
><span class="sk-expandable" data-packager="pip" data-os="mac">Install Python 3 using <a href="https://brew.sh/">homebrew</a> (<code>brew install python</code>) or by manually installing the package from <a href="https://www.python.org">https://www.python.org</a>.</span
><span class="sk-expandable" data-packager="pip" data-os="linux">Install python3 and python3-pip using the package manager of the Linux Distribution.</span
><span class="sk-expandable" data-packager="conda"
>Install conda using the <a href="https://docs.conda.io/projects/conda/en/latest/user-guide/install/">Anaconda or miniconda</a>
installers or the <a href="https://https://github.com/conda-forge/miniforge#miniforge">miniforge</a> installers
(no administrator permission required for any of those).</span>
</div><p>Then run:</p>
<div class="highlight"><pre><code
><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="">python3 -m venv sklearn-venv</span
><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="">python -m venv sklearn-venv</span
><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="">python -m venv sklearn-venv</span
><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="">source sklearn-venv/bin/activate</span
><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="">source sklearn-venv/bin/activate</span
><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="">sklearn-venv\Scripts\activate</span
><span class="sk-expandable" data-packager="pip" data-venv="">pip install -U scikit-learn</span
><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="no">pip install -U scikit-learn</span
><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="no">pip install -U scikit-learn</span
><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="no">pip3 install -U scikit-learn</span
><span class="sk-expandable" data-packager="conda">conda create -n sklearn-env -c conda-forge scikit-learn</span
><span class="sk-expandable" data-packager="conda">conda activate sklearn-env</span
></code></pre></div><p>In order to check your installation you can use</p>
<div class="highlight"><pre><code
><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="no">python3 -m pip show scikit-learn # to see which version and where scikit-learn is installed</span
><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="no">python3 -m pip freeze # to see all packages installed in the active virtualenv</span
><span class="sk-expandable" data-packager="pip" data-os="linux" data-venv="no">python3 -c "import sklearn; sklearn.show_versions()"</span
><span class="sk-expandable" data-packager="pip" data-venv="">python -m pip show scikit-learn # to see which version and where scikit-learn is installed</span
><span class="sk-expandable" data-packager="pip" data-venv="">python -m pip freeze # to see all packages installed in the active virtualenv</span
><span class="sk-expandable" data-packager="pip" data-venv="">python -c "import sklearn; sklearn.show_versions()"</span
><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="no">python -m pip show scikit-learn # to see which version and where scikit-learn is installed</span
><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="no">python -m pip freeze # to see all packages installed in the active virtualenv</span
><span class="sk-expandable" data-packager="pip" data-os="windows" data-venv="no">python -c "import sklearn; sklearn.show_versions()"</span
><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="no">python -m pip show scikit-learn # to see which version and where scikit-learn is installed</span
><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="no">python -m pip freeze # to see all packages installed in the active virtualenv</span
><span class="sk-expandable" data-packager="pip" data-os="mac" data-venv="no">python -c "import sklearn; sklearn.show_versions()"</span
><span class="sk-expandable" data-packager="conda">conda list scikit-learn # to see which scikit-learn version is installed</span
><span class="sk-expandable" data-packager="conda">conda list # to see all packages installed in the active conda environment</span
><span class="sk-expandable" data-packager="conda">python -c "import sklearn; sklearn.show_versions()"</span
></code></pre></div>
</div><p>Note that in order to avoid potential conflicts with other packages it is
strongly recommended to use a <a class="reference external" href="https://docs.python.org/3/tutorial/venv.html">virtual environment (venv)</a> or a <a class="reference external" href="https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html">conda environment</a>.</p>
<p>Using such an isolated environment 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 is it
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 start with “plot_”
and classes end with “Display”) 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>
<table class="docutils align-default">
<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>1.17.3</p></td>
<td><p>build, install</p></td>
</tr>
<tr class="row-odd"><td><p>scipy</p></td>
<td><p>1.5.0</p></td>
<td><p>build, install</p></td>
</tr>
<tr class="row-even"><td><p>joblib</p></td>
<td><p>1.1.1</p></td>
<td><p>install</p></td>
</tr>
<tr class="row-odd"><td><p>threadpoolctl</p></td>
<td><p>2.0.0</p></td>
<td><p>install</p></td>
</tr>
<tr class="row-even"><td><p>cython</p></td>
<td><p>0.29.33</p></td>
<td><p>build</p></td>
</tr>
<tr class="row-odd"><td><p>matplotlib</p></td>
<td><p>3.1.3</p></td>
<td><p>benchmark, docs, examples, tests</p></td>
</tr>
<tr class="row-even"><td><p>scikit-image</p></td>
<td><p>0.16.2</p></td>
<td><p>docs, examples, tests</p></td>
</tr>
<tr class="row-odd"><td><p>pandas</p></td>
<td><p>1.0.5</p></td>
<td><p>benchmark, docs, examples, tests</p></td>
</tr>
<tr class="row-even"><td><p>seaborn</p></td>
<td><p>0.9.0</p></td>
<td><p>docs, examples</p></td>
</tr>
<tr class="row-odd"><td><p>memory_profiler</p></td>
<td><p>0.57.0</p></td>
<td><p>benchmark, docs</p></td>
</tr>
<tr class="row-even"><td><p>pytest</p></td>
<td><p>7.1.2</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-odd"><td><p>pytest-cov</p></td>
<td><p>2.9.0</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-even"><td><p>ruff</p></td>
<td><p>0.0.272</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-odd"><td><p>black</p></td>
<td><p>23.3.0</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-even"><td><p>mypy</p></td>
<td><p>1.3</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-odd"><td><p>pyamg</p></td>
<td><p>4.0.0</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-even"><td><p>polars</p></td>
<td><p>0.18.2</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-odd"><td><p>pyarrow</p></td>
<td><p>12.0.0</p></td>
<td><p>tests</p></td>
</tr>
<tr class="row-even"><td><p>sphinx</p></td>
<td><p>6.0.0</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-odd"><td><p>sphinx-copybutton</p></td>
<td><p>0.5.2</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-even"><td><p>sphinx-gallery</p></td>
<td><p>0.10.1</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-odd"><td><p>numpydoc</p></td>
<td><p>1.2.0</p></td>
<td><p>docs, tests</p></td>
</tr>
<tr class="row-even"><td><p>Pillow</p></td>
<td><p>7.1.2</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-odd"><td><p>pooch</p></td>
<td><p>1.6.0</p></td>
<td><p>docs, examples, tests</p></td>
</tr>
<tr class="row-even"><td><p>sphinx-prompt</p></td>
<td><p>1.3.0</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-odd"><td><p>sphinxext-opengraph</p></td>
<td><p>0.4.2</p></td>
<td><p>docs</p></td>
</tr>
<tr class="row-even"><td><p>plotly</p></td>
<td><p>5.14.0</p></td>
<td><p>docs, examples</p></td>
</tr>
<tr class="row-odd"><td><p>conda-lock</p></td>
<td><p>2.0.0</p></td>
<td><p>maintenance</p></td>
</tr>
</tbody>
</table>
<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 require Python 3.6 or newer.
Scikit-learn 1.0 supported Python 3.7-3.10.
Scikit-learn 1.1 and later requires Python 3.8 or newer.</p>
</div>
</section>
<section id="installing-on-apple-silicon-m1-hardware">
<span id="install-on-apple-silicon-m1"></span><h2>Installing on Apple Silicon M1 hardware<a class="headerlink" href="#installing-on-apple-silicon-m1-hardware" title="Permalink to this heading">¶</a></h2>
<p>The recently introduced <code class="docutils literal notranslate"><span class="pre">macos/arm64</span></code> platform (sometimes also known as
<code class="docutils literal notranslate"><span class="pre">macos/aarch64</span></code>) requires the open source community to upgrade the build
configuration and automation to properly support it.</p>
<p>At the time of writing (January 2021), the only way to get a working
installation of scikit-learn on this hardware is to install scikit-learn and its
dependencies from the conda-forge distribution, for instance using the miniforge
installers:</p>
<p><a class="reference external" href="https://github.com/conda-forge/miniforge">https://github.com/conda-forge/miniforge</a></p>
<p>The following issue tracks progress on making it possible to install
scikit-learn from PyPI with pip:</p>
<p><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues/19137">https://github.com/scikit-learn/scikit-learn/issues/19137</a></p>
</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="Permalink 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="Permalink 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><style type="text/css">
span.prompt1:before {
content: "$ ";
}
</style><span class="prompt1">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="Permalink 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="prompt1">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="Permalink 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">python3-sklearn-doc</span></code> (documentation).
Only the Python 3 version is available in the Debian Buster (the more recent
Debian distribution).
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="prompt1">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>python3-sklearn-doc</span>
</pre></div></div></section>
<section id="fedora">
<h3>Fedora<a class="headerlink" href="#fedora" title="Permalink 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 Fedora30.
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="prompt1">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="Permalink to this heading">¶</a></h3>
<p>scikit-learn is available via <a class="reference external" href="http://pkgsrc-wip.sourceforge.net/">pkgsrc-wip</a>:</p>
<blockquote>
<div><p><a class="reference external" href="https://pkgsrc.se/math/py-scikit-learn">https://pkgsrc.se/math/py-scikit-learn</a></p>
</div></blockquote>
</section>
<section id="macports-for-mac-osx">
<h3>MacPorts for Mac OSX<a class="headerlink" href="#macports-for-mac-osx" title="Permalink 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="prompt1">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="Permalink 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="Permalink 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="prompt1">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/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><span class="prompt1">from<span class="w"> </span>sklearnex.neighbors<span class="w"> </span>import<span class="w"> </span>NearestNeighbors</span>
</pre></div></div><p>Compatibility with the standard scikit-learn solvers is checked by running the
full scikit-learn test suite via automated continuous integration as reported
on <a class="reference external" href="https://github.com/intel/scikit-learn-intelex">https://github.com/intel/scikit-learn-intelex</a>. If you observe any issue
with <code class="docutils literal notranslate"><span class="pre">scikit-learn-intelex</span></code>, please report the issue on their
<a class="reference external" href="https://github.com/intel/scikit-learn-intelex/issues">issue tracker</a>.</p>
</section>
<section id="winpython-for-windows">
<h3>WinPython for Windows<a class="headerlink" href="#winpython-for-windows" title="Permalink to this heading">¶</a></h3>
<p>The <a class="reference external" href="https://winpython.github.io/">WinPython</a> project distributes
scikit-learn as an additional plugin.</p>
</section>
</section>
<section id="troubleshooting">
<h2>Troubleshooting<a class="headerlink" href="#troubleshooting" title="Permalink to this heading">¶</a></h2>
<section id="error-caused-by-file-path-length-limit-on-windows">
<span id="windows-longpath"></span><h3>Error caused by file path length limit on Windows<a class="headerlink" href="#error-caused-by-file-path-length-limit-on-windows" title="Permalink to this heading">¶</a></h3>
<p>It can happen that pip fails to install packages when reaching the default path
size limit of Windows if Python is installed in a nested location such as the
<code class="docutils literal notranslate"><span class="pre">AppData</span></code> folder structure under the user home directory, for instance:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">C</span><span class="p">:</span>\<span class="n">Users</span>\<span class="n">username</span><span class="o">></span><span class="n">C</span><span class="p">:</span>\<span class="n">Users</span>\<span class="n">username</span>\<span class="n">AppData</span>\<span class="n">Local</span>\<span class="n">Microsoft</span>\<span class="n">WindowsApps</span>\<span class="n">python</span><span class="o">.</span><span class="n">exe</span> <span class="o">-</span><span class="n">m</span> <span class="n">pip</span> <span class="n">install</span> <span class="n">scikit</span><span class="o">-</span><span class="n">learn</span>
<span class="n">Collecting</span> <span class="n">scikit</span><span class="o">-</span><span class="n">learn</span>
<span class="o">...</span>
<span class="n">Installing</span> <span class="n">collected</span> <span class="n">packages</span><span class="p">:</span> <span class="n">scikit</span><span class="o">-</span><span class="n">learn</span>
<span class="n">ERROR</span><span class="p">:</span> <span class="n">Could</span> <span class="ow">not</span> <span class="n">install</span> <span class="n">packages</span> <span class="n">due</span> <span class="n">to</span> <span class="n">an</span> <span class="ne">OSError</span><span class="p">:</span> <span class="p">[</span><span class="n">Errno</span> <span class="mi">2</span><span class="p">]</span> <span class="n">No</span> <span class="n">such</span> <span class="n">file</span> <span class="ow">or</span> <span class="n">directory</span><span class="p">:</span> <span class="s1">'C:</span><span class="se">\\</span><span class="s1">Users</span><span class="se">\\</span><span class="s1">username</span><span class="se">\\</span><span class="s1">AppData</span><span class="se">\\</span><span class="s1">Local</span><span class="se">\\</span><span class="s1">Packages</span><span class="se">\\</span><span class="s1">PythonSoftwareFoundation.Python.3.7_qbz5n2kfra8p0</span><span class="se">\\</span><span class="s1">LocalCache</span><span class="se">\\</span><span class="s1">local-packages</span><span class="se">\\</span><span class="s1">Python37</span><span class="se">\\</span><span class="s1">site-packages</span><span class="se">\\</span><span class="s1">sklearn</span><span class="se">\\</span><span class="s1">datasets</span><span class="se">\\</span><span class="s1">tests</span><span class="se">\\</span><span class="s1">data</span><span class="se">\\</span><span class="s1">openml</span><span class="se">\\</span><span class="s1">292</span><span class="se">\\</span><span class="s1">api-v1-json-data-list-data_name-australian-limit-2-data_version-1-status-deactivated.json.gz'</span>
</pre></div>
</div>
<p>In this case it is possible to lift that limit in the Windows registry by
using the <code class="docutils literal notranslate"><span class="pre">regedit</span></code> tool:</p>
<ol class="arabic simple">
<li><p>Type “regedit” in the Windows start menu to launch <code class="docutils literal notranslate"><span class="pre">regedit</span></code>.</p></li>
<li><p>Go to the
<code class="docutils literal notranslate"><span class="pre">Computer\HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\FileSystem</span></code>
key.</p></li>
<li><p>Edit the value of the <code class="docutils literal notranslate"><span class="pre">LongPathsEnabled</span></code> property of that key and set
it to 1.</p></li>
<li><p>Reinstall scikit-learn (ignoring the previous broken installation):</p></li>
</ol>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1"><span class="n">pip</span> <span class="n">install</span> <span class="o">--</span><span class="n">exists</span><span class="o">-</span><span class="n">action</span><span class="o">=</span><span class="n">i</span> <span class="n">scikit</span><span class="o">-</span><span class="n">learn</span></span>
</pre></div></div></section>
</section>
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