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convergence_best
BayesNet/html/bayesnet/ensembles/AODE.cc.gcov.html

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<td width="10%" class="headerItem">Current view:</td>
<td width="10%" class="headerValue"><a href="../../index.html">top level</a> - <a href="index.html">bayesnet/ensembles</a> - AODE.cc<span style="font-size: 80%;"> (source / <a href="AODE.cc.func-c.html">functions</a>)</span></td>
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<td width="5%" class="headerCovTableHead">Coverage</td>
<td width="5%" class="headerCovTableHead" title="Covered + Uncovered code">Total</td>
<td width="5%" class="headerCovTableHead" title="Exercised code only">Hit</td>
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<td class="headerItem">Test:</td>
<td class="headerValue">coverage.info</td>
<td></td>
<td class="headerItem">Lines:</td>
<td class="headerCovTableEntryHi">100.0&nbsp;%</td>
<td class="headerCovTableEntry">20</td>
<td class="headerCovTableEntry">20</td>
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<td class="headerItem">Test Date:</td>
<td class="headerValue">2024-04-30 13:59:18</td>
<td></td>
<td class="headerItem">Functions:</td>
<td class="headerCovTableEntryHi">100.0&nbsp;%</td>
<td class="headerCovTableEntry">4</td>
<td class="headerCovTableEntry">4</td>
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<pre class="sourceHeading"> Line data Source code</pre>
<pre class="source">
<span id="L1"><span class="lineNum"> 1</span> : // ***************************************************************</span>
<span id="L2"><span class="lineNum"> 2</span> : // SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez</span>
<span id="L3"><span class="lineNum"> 3</span> : // SPDX-FileType: SOURCE</span>
<span id="L4"><span class="lineNum"> 4</span> : // SPDX-License-Identifier: MIT</span>
<span id="L5"><span class="lineNum"> 5</span> : // ***************************************************************</span>
<span id="L6"><span class="lineNum"> 6</span> : </span>
<span id="L7"><span class="lineNum"> 7</span> : #include &quot;AODE.h&quot;</span>
<span id="L8"><span class="lineNum"> 8</span> : </span>
<span id="L9"><span class="lineNum"> 9</span> : namespace bayesnet {</span>
<span id="L10"><span class="lineNum"> 10</span> <span class="tlaGNC tlaBgGNC"> 114 : AODE::AODE(bool predict_voting) : Ensemble(predict_voting)</span></span>
<span id="L11"><span class="lineNum"> 11</span> : {</span>
<span id="L12"><span class="lineNum"> 12</span> <span class="tlaGNC"> 228 : validHyperparameters = { &quot;predict_voting&quot; };</span></span>
<span id="L13"><span class="lineNum"> 13</span> : </span>
<span id="L14"><span class="lineNum"> 14</span> <span class="tlaGNC"> 342 : }</span></span>
<span id="L15"><span class="lineNum"> 15</span> <span class="tlaGNC"> 6 : void AODE::setHyperparameters(const nlohmann::json&amp; hyperparameters_)</span></span>
<span id="L16"><span class="lineNum"> 16</span> : {</span>
<span id="L17"><span class="lineNum"> 17</span> <span class="tlaGNC"> 6 : auto hyperparameters = hyperparameters_;</span></span>
<span id="L18"><span class="lineNum"> 18</span> <span class="tlaGNC"> 6 : if (hyperparameters.contains(&quot;predict_voting&quot;)) {</span></span>
<span id="L19"><span class="lineNum"> 19</span> <span class="tlaGNC"> 6 : predict_voting = hyperparameters[&quot;predict_voting&quot;];</span></span>
<span id="L20"><span class="lineNum"> 20</span> <span class="tlaGNC"> 6 : hyperparameters.erase(&quot;predict_voting&quot;);</span></span>
<span id="L21"><span class="lineNum"> 21</span> : }</span>
<span id="L22"><span class="lineNum"> 22</span> <span class="tlaGNC"> 6 : Classifier::setHyperparameters(hyperparameters);</span></span>
<span id="L23"><span class="lineNum"> 23</span> <span class="tlaGNC"> 6 : }</span></span>
<span id="L24"><span class="lineNum"> 24</span> <span class="tlaGNC"> 36 : void AODE::buildModel(const torch::Tensor&amp; weights)</span></span>
<span id="L25"><span class="lineNum"> 25</span> : {</span>
<span id="L26"><span class="lineNum"> 26</span> <span class="tlaGNC"> 36 : models.clear();</span></span>
<span id="L27"><span class="lineNum"> 27</span> <span class="tlaGNC"> 36 : significanceModels.clear();</span></span>
<span id="L28"><span class="lineNum"> 28</span> <span class="tlaGNC"> 282 : for (int i = 0; i &lt; features.size(); ++i) {</span></span>
<span id="L29"><span class="lineNum"> 29</span> <span class="tlaGNC"> 246 : models.push_back(std::make_unique&lt;SPODE&gt;(i));</span></span>
<span id="L30"><span class="lineNum"> 30</span> : }</span>
<span id="L31"><span class="lineNum"> 31</span> <span class="tlaGNC"> 36 : n_models = models.size();</span></span>
<span id="L32"><span class="lineNum"> 32</span> <span class="tlaGNC"> 36 : significanceModels = std::vector&lt;double&gt;(n_models, 1.0);</span></span>
<span id="L33"><span class="lineNum"> 33</span> <span class="tlaGNC"> 36 : }</span></span>
<span id="L34"><span class="lineNum"> 34</span> <span class="tlaGNC"> 6 : std::vector&lt;std::string&gt; AODE::graph(const std::string&amp; title) const</span></span>
<span id="L35"><span class="lineNum"> 35</span> : {</span>
<span id="L36"><span class="lineNum"> 36</span> <span class="tlaGNC"> 6 : return Ensemble::graph(title);</span></span>
<span id="L37"><span class="lineNum"> 37</span> : }</span>
<span id="L38"><span class="lineNum"> 38</span> : }</span>
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