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<h1>License<a class="headerlink" href="#license" title="Permalink to this headline">¶</a></h1>
<p>Scikit-multilearn follows the widely employed copyleft licensing of the scikit
community and is licensed BSD 2-Clause “Simplified” License. You can:</p>
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<li>Use, copy and distribute the unmodified source or binary forms of the licensed program</li>
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<h2>GPL library dependency<a class="headerlink" href="#gpl-library-dependency" title="Permalink to this headline">¶</a></h2>
<p>Some of the sub-functionalities of the library uses and depends on GPL-licensed libraries:</p>
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<li><code class="xref py py-mod docutils literal notranslate"><span class="pre">skmultilearn.cluster.graphtool</span></code> depends on GPL licensed <a class="reference external" href="https://graph-tool.skewed.de/">python-graphtool</a> module for Stochastic Blockmodel functionality</li>
<li><code class="xref py py-mod docutils literal notranslate"><span class="pre">skmultilearn.cluster.igraph</span></code> depends on GPL licensed <a class="reference external" href="http://igraph.org/python/">python-igraph</a> module for community detection methods</li>
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<p>Using any of these modules incurs GPL on your codebase, thus for commercial purposes for network-based label space division
you should be using the <code class="xref py py-mod docutils literal notranslate"><span class="pre">skmultilearn.cluster.networkx</span></code> module which is depends on the well known BSD-licensed liibrary <a class="reference external" href="https://networkx.github.io">NetworkX</a>.</p>
<p>Note that none of these libraries are installed by default.</p>
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        <p>If you use scikit-multilearn in your research and publish it, please consider citing us, it will help us get funding for making the library better. The paper is available on <a href="https://arxiv.org/abs/1702.01460">arXiv</a>, to cite it try the Bibtex code on the right.</p>
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