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<div class="section" id="module-pebl.learner.exhaustive">
<span id="learner-exhaustive-exhaustive-learners"></span><h1><tt class="xref py py-mod docutils literal"><span class="pre">learner.exhaustive</span></tt> – Exhaustive learners<a class="headerlink" href="#module-pebl.learner.exhaustive" title="Permalink to this headline">¶</a></h1>
<p>This modules provides exhaustive learners. Currently, it include the
ListLearner class which scores a list of networks. In the future, we might
implent exhaustive learners that score all possible networks meeting some
constraints (as defined by prior models).</p>
<div class="section" id="configuration-parameters">
<h2>Configuration Parameters<a class="headerlink" href="#configuration-parameters" title="Permalink to this headline">¶</a></h2>
<dl class="confparam">
<dt id="confparam-listlearner.networks">
<tt class="descname">listlearner.networks</tt><a class="headerlink" href="#confparam-listlearner.networks" title="Permalink to this definition">¶</a></dt>
<dd><p>List of networks to score.
default=</p>
</dd></dl>
</div>
<div class="section" id="listlearner-class">
<h2>ListLearner Class<a class="headerlink" href="#listlearner-class" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="pebl.learner.exhaustive.ListLearner">
<em class="property">class </em><tt class="descclassname">pebl.learner.exhaustive.</tt><tt class="descname">ListLearner</tt><big>(</big><em>data_=None</em>, <em>prior_=None</em>, <em>networks=None</em><big>)</big><a class="headerlink" href="#pebl.learner.exhaustive.ListLearner" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a ListLearner learner.</p>
<p>networks should be a list of networks (as network.Network instances).</p>
<dl class="method">
<dt id="pebl.learner.exhaustive.ListLearner.split">
<tt class="descname">split</tt><big>(</big><em>count</em><big>)</big><a class="headerlink" href="#pebl.learner.exhaustive.ListLearner.split" title="Permalink to this definition">¶</a></dt>
<dd><p>Split the learner into multiple learners.</p>
<p>Splits self.networks into <cite>count</cite> parts. This is similar to MPI’s
scatter functionality.</p>
</dd></dl>
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<li><a class="reference internal" href="#"><tt class="docutils literal"><span class="pre">learner.exhaustive</span></tt> – Exhaustive learners</a><ul>
<li><a class="reference internal" href="#configuration-parameters">Configuration Parameters</a></li>
<li><a class="reference internal" href="#listlearner-class">ListLearner Class</a></li>
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<p class="topless"><a href="../evaluator.html"
title="previous chapter"><tt class="docutils literal docutils literal docutils literal"><span class="pre">evaluator</span></tt> – Network evaluators</a></p>
<h4>Next topic</h4>
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title="next chapter"><tt class="docutils literal"><span class="pre">learner.greedy</span></tt> – Greedy learner</a></p>
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