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<li class="navelem"><a class="el" href="dir_d44c64559bbebec7f509842c48db8b23.html">include</a></li><li class="navelem"><a class="el" href="dir_daf582bc00f2bbc6516ddb6630e28009.html">svm_classifier</a></li> </ul>
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<div class="headertitle"><div class="title">kernel_parameters.hpp</div></div>
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<div class="contents">
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<div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno"> 1</span><span class="preprocessor">#pragma once</span></div>
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<div class="line"><a id="l00002" name="l00002"></a><span class="lineno"> 2</span> </div>
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<div class="line"><a id="l00003" name="l00003"></a><span class="lineno"> 3</span><span class="preprocessor">#include "types.hpp"</span></div>
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<div class="line"><a id="l00004" name="l00004"></a><span class="lineno"> 4</span><span class="preprocessor">#include <torch/torch.h></span></div>
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<div class="line"><a id="l00005" name="l00005"></a><span class="lineno"> 5</span><span class="preprocessor">#include <vector></span></div>
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<div class="line"><a id="l00006" name="l00006"></a><span class="lineno"> 6</span><span class="preprocessor">#include <memory></span></div>
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<div class="line"><a id="l00007" name="l00007"></a><span class="lineno"> 7</span> </div>
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<div class="line"><a id="l00008" name="l00008"></a><span class="lineno"> 8</span><span class="comment">// Forward declarations for libsvm and liblinear structures</span></div>
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<div class="line"><a id="l00009" name="l00009"></a><span class="lineno"> 9</span><span class="keyword">struct </span>svm_node;</div>
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<div class="line"><a id="l00010" name="l00010"></a><span class="lineno"> 10</span><span class="keyword">struct </span>svm_problem;</div>
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<div class="line"><a id="l00011" name="l00011"></a><span class="lineno"> 11</span><span class="keyword">struct </span>feature_node;</div>
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<div class="line"><a id="l00012" name="l00012"></a><span class="lineno"> 12</span><span class="keyword">struct </span>problem;</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="keyword">namespace </span>svm_classifier {</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="l00023" name="l00023"></a><span class="lineno"> 23</span> <span class="keyword">class </span>DataConverter {</div>
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<div class="line"><a id="l00024" name="l00024"></a><span class="lineno"> 24</span> <span class="keyword">public</span>:</div>
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<div class="line"><a id="l00028" name="l00028"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a5874904555f26448ed5ae4cf6f370056"> 28</a></span> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a5874904555f26448ed5ae4cf6f370056">DataConverter</a>();</div>
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<div class="line"><a id="l00029" name="l00029"></a><span class="lineno"> 29</span> </div>
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<div class="line"><a id="l00033" name="l00033"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#ac3af2c9c03cffe2968f29147611e333d"> 33</a></span> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#ac3af2c9c03cffe2968f29147611e333d">~DataConverter</a>();</div>
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<div class="line"><a id="l00034" name="l00034"></a><span class="lineno"> 34</span> </div>
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<div class="line"><a id="l00041" name="l00041"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a66f446e4decfe47bbba37c789f03f729"> 41</a></span> std::unique_ptr<svm_problem> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a66f446e4decfe47bbba37c789f03f729">to_svm_problem</a>(<span class="keyword">const</span> torch::Tensor& X,</div>
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<div class="line"><a id="l00042" name="l00042"></a><span class="lineno"> 42</span> <span class="keyword">const</span> torch::Tensor& y = torch::Tensor());</div>
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<div class="line"><a id="l00043" name="l00043"></a><span class="lineno"> 43</span> </div>
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<div class="line"><a id="l00050" name="l00050"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a7e7d8f6102b7a9b3256ff0dc6f536a35"> 50</a></span> std::unique_ptr<problem> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a7e7d8f6102b7a9b3256ff0dc6f536a35">to_linear_problem</a>(<span class="keyword">const</span> torch::Tensor& X,</div>
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<div class="line"><a id="l00051" name="l00051"></a><span class="lineno"> 51</span> <span class="keyword">const</span> torch::Tensor& y = torch::Tensor());</div>
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<div class="line"><a id="l00052" name="l00052"></a><span class="lineno"> 52</span> </div>
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<div class="line"><a id="l00058" name="l00058"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a16e1539ef1266ca9ddd27a2ac5a53b92"> 58</a></span> svm_node* <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a16e1539ef1266ca9ddd27a2ac5a53b92">to_svm_node</a>(<span class="keyword">const</span> torch::Tensor& sample);</div>
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<div class="line"><a id="l00059" name="l00059"></a><span class="lineno"> 59</span> </div>
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||||
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a6bb2b4565b27df0db5f229dbd380795e"> 65</a></span> feature_node* <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a6bb2b4565b27df0db5f229dbd380795e">to_feature_node</a>(<span class="keyword">const</span> torch::Tensor& sample);</div>
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<div class="line"><a id="l00066" name="l00066"></a><span class="lineno"> 66</span> </div>
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<div class="line"><a id="l00072" name="l00072"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#ab3e800a5016a915e9912d5873bb48741"> 72</a></span> torch::Tensor <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#ab3e800a5016a915e9912d5873bb48741">from_predictions</a>(<span class="keyword">const</span> std::vector<double>& predictions);</div>
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<div class="line"><a id="l00073" name="l00073"></a><span class="lineno"> 73</span> </div>
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<div class="line"><a id="l00079" name="l00079"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a5460485675613c54596418af3d5057ff"> 79</a></span> torch::Tensor <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a5460485675613c54596418af3d5057ff">from_probabilities</a>(<span class="keyword">const</span> std::vector<std::vector<double>>& probabilities);</div>
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<div class="line"><a id="l00080" name="l00080"></a><span class="lineno"> 80</span> </div>
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||||
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a503eba54e8bb1f370e04b6e24354a32f"> 86</a></span> torch::Tensor <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a503eba54e8bb1f370e04b6e24354a32f">from_decision_values</a>(<span class="keyword">const</span> std::vector<std::vector<double>>& decision_values);</div>
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<div class="line"><a id="l00087" name="l00087"></a><span class="lineno"> 87</span> </div>
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<div class="line"><a id="l00094" name="l00094"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#aa0615f3de29958b2c5229d349f2f60ce"> 94</a></span> <span class="keywordtype">void</span> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#aa0615f3de29958b2c5229d349f2f60ce">validate_tensors</a>(<span class="keyword">const</span> torch::Tensor& X, <span class="keyword">const</span> torch::Tensor& y = torch::Tensor());</div>
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<div class="line"><a id="l00095" name="l00095"></a><span class="lineno"> 95</span> </div>
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||||
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a26342a8cc8b943f099112040aa960ae6"> 100</a></span> <span class="keywordtype">int</span> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a26342a8cc8b943f099112040aa960ae6">get_n_features</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> n_features_; }</div>
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<div class="line"><a id="l00101" name="l00101"></a><span class="lineno"> 101</span> </div>
|
||||
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a16999ded27bc2d42d2ebd9551b00c1cb"> 106</a></span> <span class="keywordtype">int</span> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a16999ded27bc2d42d2ebd9551b00c1cb">get_n_samples</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> n_samples_; }</div>
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||||
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno"> 107</span> </div>
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||||
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a46d12ba28c4c5bf6e0fad1122c621fa8"> 111</a></span> <span class="keywordtype">void</span> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a46d12ba28c4c5bf6e0fad1122c621fa8">cleanup</a>();</div>
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||||
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno"> 112</span> </div>
|
||||
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a9259322e54d2477478a684e99d8e557a"> 117</a></span> <span class="keywordtype">void</span> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a9259322e54d2477478a684e99d8e557a">set_sparse_threshold</a>(<span class="keywordtype">double</span> threshold) { sparse_threshold_ = threshold; }</div>
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||||
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno"> 118</span> </div>
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<div class="line"><a id="l00123" name="l00123"></a><span class="lineno"><a class="line" href="classsvm__classifier_1_1DataConverter.html#a1905f60fef9ffd3a8e8e45e41395352d"> 123</a></span> <span class="keywordtype">double</span> <a class="code hl_function" href="classsvm__classifier_1_1DataConverter.html#a1905f60fef9ffd3a8e8e45e41395352d">get_sparse_threshold</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> sparse_threshold_; }</div>
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<div class="line"><a id="l00124" name="l00124"></a><span class="lineno"> 124</span> </div>
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<div class="line"><a id="l00125" name="l00125"></a><span class="lineno"> 125</span> <span class="keyword">private</span>:</div>
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<div class="line"><a id="l00126" name="l00126"></a><span class="lineno"> 126</span> <span class="keywordtype">int</span> n_features_; </div>
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||||
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno"> 127</span> <span class="keywordtype">int</span> n_samples_; </div>
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<div class="line"><a id="l00128" name="l00128"></a><span class="lineno"> 128</span> <span class="keywordtype">double</span> sparse_threshold_; </div>
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<div class="line"><a id="l00129" name="l00129"></a><span class="lineno"> 129</span> </div>
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<div class="line"><a id="l00130" name="l00130"></a><span class="lineno"> 130</span> <span class="comment">// Memory management for libsvm structures</span></div>
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<div class="line"><a id="l00131" name="l00131"></a><span class="lineno"> 131</span> std::vector<std::vector<svm_node>> svm_nodes_storage_;</div>
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<div class="line"><a id="l00132" name="l00132"></a><span class="lineno"> 132</span> std::vector<svm_node*> svm_x_space_;</div>
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<div class="line"><a id="l00133" name="l00133"></a><span class="lineno"> 133</span> std::vector<double> svm_y_space_;</div>
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<div class="line"><a id="l00134" name="l00134"></a><span class="lineno"> 134</span> </div>
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<div class="line"><a id="l00135" name="l00135"></a><span class="lineno"> 135</span> <span class="comment">// Memory management for liblinear structures</span></div>
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<div class="line"><a id="l00136" name="l00136"></a><span class="lineno"> 136</span> std::vector<std::vector<feature_node>> linear_nodes_storage_;</div>
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<div class="line"><a id="l00137" name="l00137"></a><span class="lineno"> 137</span> std::vector<feature_node*> linear_x_space_;</div>
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<div class="line"><a id="l00138" name="l00138"></a><span class="lineno"> 138</span> std::vector<double> linear_y_space_;</div>
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<div class="line"><a id="l00139" name="l00139"></a><span class="lineno"> 139</span> </div>
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<div class="line"><a id="l00140" name="l00140"></a><span class="lineno"> 140</span> <span class="comment">// Single sample storage (for prediction)</span></div>
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<div class="line"><a id="l00141" name="l00141"></a><span class="lineno"> 141</span> std::vector<svm_node> single_svm_nodes_;</div>
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<div class="line"><a id="l00142" name="l00142"></a><span class="lineno"> 142</span> std::vector<feature_node> single_linear_nodes_;</div>
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<div class="line"><a id="l00143" name="l00143"></a><span class="lineno"> 143</span> </div>
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<div class="line"><a id="l00149" name="l00149"></a><span class="lineno"> 149</span> std::vector<std::vector<svm_node>> tensor_to_svm_nodes(<span class="keyword">const</span> torch::Tensor& X);</div>
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<div class="line"><a id="l00150" name="l00150"></a><span class="lineno"> 150</span> </div>
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<div class="line"><a id="l00156" name="l00156"></a><span class="lineno"> 156</span> std::vector<std::vector<feature_node>> tensor_to_linear_nodes(<span class="keyword">const</span> torch::Tensor& X);</div>
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<div class="line"><a id="l00157" name="l00157"></a><span class="lineno"> 157</span> </div>
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<div class="line"><a id="l00163" name="l00163"></a><span class="lineno"> 163</span> std::vector<svm_node> sample_to_svm_nodes(<span class="keyword">const</span> torch::Tensor& sample);</div>
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<div class="line"><a id="l00164" name="l00164"></a><span class="lineno"> 164</span> </div>
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<div class="line"><a id="l00170" name="l00170"></a><span class="lineno"> 170</span> std::vector<feature_node> sample_to_linear_nodes(<span class="keyword">const</span> torch::Tensor& sample);</div>
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<div class="line"><a id="l00171" name="l00171"></a><span class="lineno"> 171</span> </div>
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<div class="line"><a id="l00177" name="l00177"></a><span class="lineno"> 177</span> std::vector<double> extract_labels(<span class="keyword">const</span> torch::Tensor& y);</div>
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<div class="line"><a id="l00178" name="l00178"></a><span class="lineno"> 178</span> </div>
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<div class="line"><a id="l00184" name="l00184"></a><span class="lineno"> 184</span> torch::Tensor ensure_cpu_tensor(<span class="keyword">const</span> torch::Tensor& tensor);</div>
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<div class="line"><a id="l00185" name="l00185"></a><span class="lineno"> 185</span> </div>
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<div class="line"><a id="l00192" name="l00192"></a><span class="lineno"> 192</span> <span class="keywordtype">void</span> validate_tensor_properties(<span class="keyword">const</span> torch::Tensor& tensor, <span class="keywordtype">int</span> expected_dims, <span class="keyword">const</span> std::string& name);</div>
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<div class="line"><a id="l00193" name="l00193"></a><span class="lineno"> 193</span> };</div>
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<div class="line"><a id="l00194" name="l00194"></a><span class="lineno"> 194</span> </div>
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<div class="line"><a id="l00195" name="l00195"></a><span class="lineno"> 195</span>} <span class="comment">// namespace svm_classifier</span></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a16999ded27bc2d42d2ebd9551b00c1cb"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a16999ded27bc2d42d2ebd9551b00c1cb">svm_classifier::DataConverter::get_n_samples</a></div><div class="ttdeci">int get_n_samples() const</div><div class="ttdoc">Get number of samples from last conversion.</div><div class="ttdef"><b>Definition</b> <a href="kernel__parameters_8hpp_source.html#l00106">kernel_parameters.hpp:106</a></div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a16e1539ef1266ca9ddd27a2ac5a53b92"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a16e1539ef1266ca9ddd27a2ac5a53b92">svm_classifier::DataConverter::to_svm_node</a></div><div class="ttdeci">svm_node * to_svm_node(const torch::Tensor &sample)</div><div class="ttdoc">Convert single sample to libsvm format.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a1905f60fef9ffd3a8e8e45e41395352d"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a1905f60fef9ffd3a8e8e45e41395352d">svm_classifier::DataConverter::get_sparse_threshold</a></div><div class="ttdeci">double get_sparse_threshold() const</div><div class="ttdoc">Get sparse threshold.</div><div class="ttdef"><b>Definition</b> <a href="kernel__parameters_8hpp_source.html#l00123">kernel_parameters.hpp:123</a></div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a26342a8cc8b943f099112040aa960ae6"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a26342a8cc8b943f099112040aa960ae6">svm_classifier::DataConverter::get_n_features</a></div><div class="ttdeci">int get_n_features() const</div><div class="ttdoc">Get number of features from last conversion.</div><div class="ttdef"><b>Definition</b> <a href="kernel__parameters_8hpp_source.html#l00100">kernel_parameters.hpp:100</a></div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a46d12ba28c4c5bf6e0fad1122c621fa8"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a46d12ba28c4c5bf6e0fad1122c621fa8">svm_classifier::DataConverter::cleanup</a></div><div class="ttdeci">void cleanup()</div><div class="ttdoc">Clean up all allocated memory.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a503eba54e8bb1f370e04b6e24354a32f"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a503eba54e8bb1f370e04b6e24354a32f">svm_classifier::DataConverter::from_decision_values</a></div><div class="ttdeci">torch::Tensor from_decision_values(const std::vector< std::vector< double > > &decision_values)</div><div class="ttdoc">Convert decision values back to PyTorch tensor.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a5460485675613c54596418af3d5057ff"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a5460485675613c54596418af3d5057ff">svm_classifier::DataConverter::from_probabilities</a></div><div class="ttdeci">torch::Tensor from_probabilities(const std::vector< std::vector< double > > &probabilities)</div><div class="ttdoc">Convert probabilities back to PyTorch tensor.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a5874904555f26448ed5ae4cf6f370056"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a5874904555f26448ed5ae4cf6f370056">svm_classifier::DataConverter::DataConverter</a></div><div class="ttdeci">DataConverter()</div><div class="ttdoc">Default constructor.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a66f446e4decfe47bbba37c789f03f729"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a66f446e4decfe47bbba37c789f03f729">svm_classifier::DataConverter::to_svm_problem</a></div><div class="ttdeci">std::unique_ptr< svm_problem > to_svm_problem(const torch::Tensor &X, const torch::Tensor &y=torch::Tensor())</div><div class="ttdoc">Convert PyTorch tensors to libsvm format.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a6bb2b4565b27df0db5f229dbd380795e"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a6bb2b4565b27df0db5f229dbd380795e">svm_classifier::DataConverter::to_feature_node</a></div><div class="ttdeci">feature_node * to_feature_node(const torch::Tensor &sample)</div><div class="ttdoc">Convert single sample to liblinear format.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a7e7d8f6102b7a9b3256ff0dc6f536a35"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a7e7d8f6102b7a9b3256ff0dc6f536a35">svm_classifier::DataConverter::to_linear_problem</a></div><div class="ttdeci">std::unique_ptr< problem > to_linear_problem(const torch::Tensor &X, const torch::Tensor &y=torch::Tensor())</div><div class="ttdoc">Convert PyTorch tensors to liblinear format.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_a9259322e54d2477478a684e99d8e557a"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#a9259322e54d2477478a684e99d8e557a">svm_classifier::DataConverter::set_sparse_threshold</a></div><div class="ttdeci">void set_sparse_threshold(double threshold)</div><div class="ttdoc">Set sparse threshold (features with absolute value below this are ignored)</div><div class="ttdef"><b>Definition</b> <a href="kernel__parameters_8hpp_source.html#l00117">kernel_parameters.hpp:117</a></div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_aa0615f3de29958b2c5229d349f2f60ce"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#aa0615f3de29958b2c5229d349f2f60ce">svm_classifier::DataConverter::validate_tensors</a></div><div class="ttdeci">void validate_tensors(const torch::Tensor &X, const torch::Tensor &y=torch::Tensor())</div><div class="ttdoc">Validate input tensors.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_ab3e800a5016a915e9912d5873bb48741"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#ab3e800a5016a915e9912d5873bb48741">svm_classifier::DataConverter::from_predictions</a></div><div class="ttdeci">torch::Tensor from_predictions(const std::vector< double > &predictions)</div><div class="ttdoc">Convert predictions back to PyTorch tensor.</div></div>
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<div class="ttc" id="aclasssvm__classifier_1_1DataConverter_html_ac3af2c9c03cffe2968f29147611e333d"><div class="ttname"><a href="classsvm__classifier_1_1DataConverter.html#ac3af2c9c03cffe2968f29147611e333d">svm_classifier::DataConverter::~DataConverter</a></div><div class="ttdeci">~DataConverter()</div><div class="ttdoc">Destructor - cleans up allocated memory.</div></div>
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