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<div id="projectname">BayesNet<span id="projectnumber"> 1.0.5</span>
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<div id="projectbrief">Bayesian Network Classifiers using libtorch from scratch</div>
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<div class="header">
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<div class="headertitle"><div class="title">A2DE.cc</div></div>
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<div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno"> 1</span><span class="comment">// ***************************************************************</span></div>
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<div class="line"><a id="l00002" name="l00002"></a><span class="lineno"> 2</span><span class="comment">// SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez</span></div>
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<div class="line"><a id="l00003" name="l00003"></a><span class="lineno"> 3</span><span class="comment">// SPDX-FileType: SOURCE</span></div>
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<div class="line"><a id="l00004" name="l00004"></a><span class="lineno"> 4</span><span class="comment">// SPDX-License-Identifier: MIT</span></div>
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<div class="line"><a id="l00005" name="l00005"></a><span class="lineno"> 5</span><span class="comment">// ***************************************************************</span></div>
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<div class="line"><a id="l00006" name="l00006"></a><span class="lineno"> 6</span> </div>
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<div class="line"><a id="l00007" name="l00007"></a><span class="lineno"> 7</span><span class="preprocessor">#include "A2DE.h"</span></div>
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<div class="line"><a id="l00008" name="l00008"></a><span class="lineno"> 8</span> </div>
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<div class="line"><a id="l00009" name="l00009"></a><span class="lineno"> 9</span><span class="keyword">namespace </span>bayesnet {</div>
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<div class="line"><a id="l00010" name="l00010"></a><span class="lineno"> 10</span> A2DE::A2DE(<span class="keywordtype">bool</span> predict_voting) : Ensemble(predict_voting)</div>
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<div class="line"><a id="l00011" name="l00011"></a><span class="lineno"> 11</span> {</div>
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<div class="line"><a id="l00012" name="l00012"></a><span class="lineno"> 12</span> validHyperparameters = { <span class="stringliteral">"predict_voting"</span> };</div>
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<div class="line"><a id="l00013" name="l00013"></a><span class="lineno"> 13</span> }</div>
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<div class="line"><a id="l00014" name="l00014"></a><span class="lineno"> 14</span> <span class="keywordtype">void</span> A2DE::setHyperparameters(<span class="keyword">const</span> nlohmann::json& hyperparameters_)</div>
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<div class="line"><a id="l00015" name="l00015"></a><span class="lineno"> 15</span> {</div>
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<div class="line"><a id="l00016" name="l00016"></a><span class="lineno"> 16</span> <span class="keyword">auto</span> hyperparameters = hyperparameters_;</div>
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<div class="line"><a id="l00017" name="l00017"></a><span class="lineno"> 17</span> <span class="keywordflow">if</span> (hyperparameters.contains(<span class="stringliteral">"predict_voting"</span>)) {</div>
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<div class="line"><a id="l00018" name="l00018"></a><span class="lineno"> 18</span> predict_voting = hyperparameters[<span class="stringliteral">"predict_voting"</span>];</div>
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<div class="line"><a id="l00019" name="l00019"></a><span class="lineno"> 19</span> hyperparameters.erase(<span class="stringliteral">"predict_voting"</span>);</div>
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<div class="line"><a id="l00020" name="l00020"></a><span class="lineno"> 20</span> }</div>
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<div class="line"><a id="l00021" name="l00021"></a><span class="lineno"> 21</span> Classifier::setHyperparameters(hyperparameters);</div>
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<div class="line"><a id="l00022" name="l00022"></a><span class="lineno"> 22</span> }</div>
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<div class="line"><a id="l00023" name="l00023"></a><span class="lineno"> 23</span> <span class="keywordtype">void</span> A2DE::buildModel(<span class="keyword">const</span> torch::Tensor& weights)</div>
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<div class="line"><a id="l00024" name="l00024"></a><span class="lineno"> 24</span> {</div>
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<div class="line"><a id="l00025" name="l00025"></a><span class="lineno"> 25</span> models.clear();</div>
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<div class="line"><a id="l00026" name="l00026"></a><span class="lineno"> 26</span> significanceModels.clear();</div>
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<div class="line"><a id="l00027" name="l00027"></a><span class="lineno"> 27</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < features.size() - 1; ++i) {</div>
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<div class="line"><a id="l00028" name="l00028"></a><span class="lineno"> 28</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = i + 1; j < features.size(); ++j) {</div>
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<div class="line"><a id="l00029" name="l00029"></a><span class="lineno"> 29</span> <span class="keyword">auto</span> model = std::make_unique<SPnDE>(std::vector<int>({ i, j }));</div>
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<div class="line"><a id="l00030" name="l00030"></a><span class="lineno"> 30</span> models.push_back(std::move(model));</div>
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<div class="line"><a id="l00031" name="l00031"></a><span class="lineno"> 31</span> }</div>
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<div class="line"><a id="l00032" name="l00032"></a><span class="lineno"> 32</span> }</div>
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<div class="line"><a id="l00033" name="l00033"></a><span class="lineno"> 33</span> n_models = <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span><span class="keyword">></span>(models.size());</div>
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<div class="line"><a id="l00034" name="l00034"></a><span class="lineno"> 34</span> significanceModels = std::vector<double>(n_models, 1.0);</div>
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<div class="line"><a id="l00035" name="l00035"></a><span class="lineno"> 35</span> }</div>
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<div class="line"><a id="l00036" name="l00036"></a><span class="lineno"> 36</span> std::vector<std::string> A2DE::graph(<span class="keyword">const</span> std::string& title)<span class="keyword"> const</span></div>
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<div class="line"><a id="l00037" name="l00037"></a><span class="lineno"> 37</span><span class="keyword"> </span>{</div>
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<div class="line"><a id="l00038" name="l00038"></a><span class="lineno"> 38</span> <span class="keywordflow">return</span> Ensemble::graph(title);</div>
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<div class="line"><a id="l00039" name="l00039"></a><span class="lineno"> 39</span> }</div>
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<div class="line"><a id="l00040" name="l00040"></a><span class="lineno"> 40</span>}</div>
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