1043 lines
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1043 lines
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<div id="projectname">SVM Classifier C++<span id="projectnumber"> 1.0.0</span>
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<div id="projectbrief">High-performance Support Vector Machine classifier with scikit-learn compatible API</div>
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<li class="navelem"><b>svm_classifier</b></li><li class="navelem"><a class="el" href="classsvm__classifier_1_1DataConverter.html">DataConverter</a></li> </ul>
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<a href="#pub-methods">Public Member Functions</a> |
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<p>Data converter between libtorch tensors and SVM library formats.
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<a href="classsvm__classifier_1_1DataConverter.html#details">More...</a></p>
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<p><code>#include <<a class="el" href="data__converter_8hpp_source.html">data_converter.hpp</a>></code></p>
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<table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="pub-methods" name="pub-methods"></a>
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Public Member Functions</h2></td></tr>
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<tr class="memitem:a5874904555f26448ed5ae4cf6f370056" id="r_a5874904555f26448ed5ae4cf6f370056"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a5874904555f26448ed5ae4cf6f370056">DataConverter</a> ()</td></tr>
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<tr class="memdesc:a5874904555f26448ed5ae4cf6f370056"><td class="mdescLeft"> </td><td class="mdescRight">Default constructor. <br /></td></tr>
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<tr class="separator:a5874904555f26448ed5ae4cf6f370056"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ac3af2c9c03cffe2968f29147611e333d" id="r_ac3af2c9c03cffe2968f29147611e333d"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#ac3af2c9c03cffe2968f29147611e333d">~DataConverter</a> ()</td></tr>
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<tr class="memdesc:ac3af2c9c03cffe2968f29147611e333d"><td class="mdescLeft"> </td><td class="mdescRight">Destructor - cleans up allocated memory. <br /></td></tr>
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<tr class="separator:ac3af2c9c03cffe2968f29147611e333d"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a66f446e4decfe47bbba37c789f03f729" id="r_a66f446e4decfe47bbba37c789f03f729"><td class="memItemLeft" align="right" valign="top">std::unique_ptr< svm_problem > </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a66f446e4decfe47bbba37c789f03f729">to_svm_problem</a> (const torch::Tensor &X, const torch::Tensor &y=torch::Tensor())</td></tr>
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<tr class="memdesc:a66f446e4decfe47bbba37c789f03f729"><td class="mdescLeft"> </td><td class="mdescRight">Convert PyTorch tensors to libsvm format. <br /></td></tr>
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<tr class="separator:a66f446e4decfe47bbba37c789f03f729"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a7e7d8f6102b7a9b3256ff0dc6f536a35" id="r_a7e7d8f6102b7a9b3256ff0dc6f536a35"><td class="memItemLeft" align="right" valign="top">std::unique_ptr< problem > </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a7e7d8f6102b7a9b3256ff0dc6f536a35">to_linear_problem</a> (const torch::Tensor &X, const torch::Tensor &y=torch::Tensor())</td></tr>
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<tr class="memdesc:a7e7d8f6102b7a9b3256ff0dc6f536a35"><td class="mdescLeft"> </td><td class="mdescRight">Convert PyTorch tensors to liblinear format. <br /></td></tr>
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<tr class="separator:a7e7d8f6102b7a9b3256ff0dc6f536a35"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a16e1539ef1266ca9ddd27a2ac5a53b92" id="r_a16e1539ef1266ca9ddd27a2ac5a53b92"><td class="memItemLeft" align="right" valign="top">svm_node * </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a16e1539ef1266ca9ddd27a2ac5a53b92">to_svm_node</a> (const torch::Tensor &sample)</td></tr>
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<tr class="memdesc:a16e1539ef1266ca9ddd27a2ac5a53b92"><td class="mdescLeft"> </td><td class="mdescRight">Convert single sample to libsvm format. <br /></td></tr>
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<tr class="separator:a16e1539ef1266ca9ddd27a2ac5a53b92"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a6bb2b4565b27df0db5f229dbd380795e" id="r_a6bb2b4565b27df0db5f229dbd380795e"><td class="memItemLeft" align="right" valign="top">feature_node * </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a6bb2b4565b27df0db5f229dbd380795e">to_feature_node</a> (const torch::Tensor &sample)</td></tr>
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<tr class="memdesc:a6bb2b4565b27df0db5f229dbd380795e"><td class="mdescLeft"> </td><td class="mdescRight">Convert single sample to liblinear format. <br /></td></tr>
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<tr class="separator:a6bb2b4565b27df0db5f229dbd380795e"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ab3e800a5016a915e9912d5873bb48741" id="r_ab3e800a5016a915e9912d5873bb48741"><td class="memItemLeft" align="right" valign="top">torch::Tensor </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#ab3e800a5016a915e9912d5873bb48741">from_predictions</a> (const std::vector< double > &predictions)</td></tr>
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<tr class="memdesc:ab3e800a5016a915e9912d5873bb48741"><td class="mdescLeft"> </td><td class="mdescRight">Convert predictions back to PyTorch tensor. <br /></td></tr>
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<tr class="separator:ab3e800a5016a915e9912d5873bb48741"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a5460485675613c54596418af3d5057ff" id="r_a5460485675613c54596418af3d5057ff"><td class="memItemLeft" align="right" valign="top">torch::Tensor </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a5460485675613c54596418af3d5057ff">from_probabilities</a> (const std::vector< std::vector< double > > &probabilities)</td></tr>
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<tr class="memdesc:a5460485675613c54596418af3d5057ff"><td class="mdescLeft"> </td><td class="mdescRight">Convert probabilities back to PyTorch tensor. <br /></td></tr>
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<tr class="separator:a5460485675613c54596418af3d5057ff"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a503eba54e8bb1f370e04b6e24354a32f" id="r_a503eba54e8bb1f370e04b6e24354a32f"><td class="memItemLeft" align="right" valign="top">torch::Tensor </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a503eba54e8bb1f370e04b6e24354a32f">from_decision_values</a> (const std::vector< std::vector< double > > &decision_values)</td></tr>
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<tr class="memdesc:a503eba54e8bb1f370e04b6e24354a32f"><td class="mdescLeft"> </td><td class="mdescRight">Convert decision values back to PyTorch tensor. <br /></td></tr>
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<tr class="separator:a503eba54e8bb1f370e04b6e24354a32f"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:aa0615f3de29958b2c5229d349f2f60ce" id="r_aa0615f3de29958b2c5229d349f2f60ce"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#aa0615f3de29958b2c5229d349f2f60ce">validate_tensors</a> (const torch::Tensor &X, const torch::Tensor &y=torch::Tensor())</td></tr>
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<tr class="memdesc:aa0615f3de29958b2c5229d349f2f60ce"><td class="mdescLeft"> </td><td class="mdescRight">Validate input tensors. <br /></td></tr>
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<tr class="separator:aa0615f3de29958b2c5229d349f2f60ce"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a26342a8cc8b943f099112040aa960ae6" id="r_a26342a8cc8b943f099112040aa960ae6"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a26342a8cc8b943f099112040aa960ae6">get_n_features</a> () const</td></tr>
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<tr class="memdesc:a26342a8cc8b943f099112040aa960ae6"><td class="mdescLeft"> </td><td class="mdescRight">Get number of features from last conversion. <br /></td></tr>
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<tr class="separator:a26342a8cc8b943f099112040aa960ae6"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a16999ded27bc2d42d2ebd9551b00c1cb" id="r_a16999ded27bc2d42d2ebd9551b00c1cb"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a16999ded27bc2d42d2ebd9551b00c1cb">get_n_samples</a> () const</td></tr>
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<tr class="memdesc:a16999ded27bc2d42d2ebd9551b00c1cb"><td class="mdescLeft"> </td><td class="mdescRight">Get number of samples from last conversion. <br /></td></tr>
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<tr class="separator:a16999ded27bc2d42d2ebd9551b00c1cb"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a46d12ba28c4c5bf6e0fad1122c621fa8" id="r_a46d12ba28c4c5bf6e0fad1122c621fa8"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a46d12ba28c4c5bf6e0fad1122c621fa8">cleanup</a> ()</td></tr>
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<tr class="memdesc:a46d12ba28c4c5bf6e0fad1122c621fa8"><td class="mdescLeft"> </td><td class="mdescRight">Clean up all allocated memory. <br /></td></tr>
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<tr class="separator:a46d12ba28c4c5bf6e0fad1122c621fa8"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a9259322e54d2477478a684e99d8e557a" id="r_a9259322e54d2477478a684e99d8e557a"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a9259322e54d2477478a684e99d8e557a">set_sparse_threshold</a> (double threshold)</td></tr>
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<tr class="memdesc:a9259322e54d2477478a684e99d8e557a"><td class="mdescLeft"> </td><td class="mdescRight">Set sparse threshold (features with absolute value below this are ignored) <br /></td></tr>
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<tr class="separator:a9259322e54d2477478a684e99d8e557a"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a1905f60fef9ffd3a8e8e45e41395352d" id="r_a1905f60fef9ffd3a8e8e45e41395352d"><td class="memItemLeft" align="right" valign="top">double </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a1905f60fef9ffd3a8e8e45e41395352d">get_sparse_threshold</a> () const</td></tr>
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<tr class="memdesc:a1905f60fef9ffd3a8e8e45e41395352d"><td class="mdescLeft"> </td><td class="mdescRight">Get sparse threshold. <br /></td></tr>
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<tr class="separator:a1905f60fef9ffd3a8e8e45e41395352d"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a5874904555f26448ed5ae4cf6f370056" id="r_a5874904555f26448ed5ae4cf6f370056"><td class="memItemLeft" align="right" valign="top"><a id="a5874904555f26448ed5ae4cf6f370056" name="a5874904555f26448ed5ae4cf6f370056"></a>
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 </td><td class="memItemRight" valign="bottom"><b>DataConverter</b> ()</td></tr>
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<tr class="memdesc:a5874904555f26448ed5ae4cf6f370056"><td class="mdescLeft"> </td><td class="mdescRight">Default constructor. <br /></td></tr>
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<tr class="separator:a5874904555f26448ed5ae4cf6f370056"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ac3af2c9c03cffe2968f29147611e333d" id="r_ac3af2c9c03cffe2968f29147611e333d"><td class="memItemLeft" align="right" valign="top"><a id="ac3af2c9c03cffe2968f29147611e333d" name="ac3af2c9c03cffe2968f29147611e333d"></a>
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 </td><td class="memItemRight" valign="bottom"><b>~DataConverter</b> ()</td></tr>
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<tr class="memdesc:ac3af2c9c03cffe2968f29147611e333d"><td class="mdescLeft"> </td><td class="mdescRight">Destructor - cleans up allocated memory. <br /></td></tr>
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<tr class="separator:ac3af2c9c03cffe2968f29147611e333d"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a66f446e4decfe47bbba37c789f03f729" id="r_a66f446e4decfe47bbba37c789f03f729"><td class="memItemLeft" align="right" valign="top">std::unique_ptr< svm_problem > </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a66f446e4decfe47bbba37c789f03f729">to_svm_problem</a> (const torch::Tensor &X, const torch::Tensor &y=torch::Tensor())</td></tr>
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<tr class="memdesc:a66f446e4decfe47bbba37c789f03f729"><td class="mdescLeft"> </td><td class="mdescRight">Convert PyTorch tensors to libsvm format. <br /></td></tr>
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<tr class="separator:a66f446e4decfe47bbba37c789f03f729"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a7e7d8f6102b7a9b3256ff0dc6f536a35" id="r_a7e7d8f6102b7a9b3256ff0dc6f536a35"><td class="memItemLeft" align="right" valign="top">std::unique_ptr< problem > </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a7e7d8f6102b7a9b3256ff0dc6f536a35">to_linear_problem</a> (const torch::Tensor &X, const torch::Tensor &y=torch::Tensor())</td></tr>
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<tr class="memdesc:a7e7d8f6102b7a9b3256ff0dc6f536a35"><td class="mdescLeft"> </td><td class="mdescRight">Convert PyTorch tensors to liblinear format. <br /></td></tr>
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<tr class="separator:a7e7d8f6102b7a9b3256ff0dc6f536a35"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a16e1539ef1266ca9ddd27a2ac5a53b92" id="r_a16e1539ef1266ca9ddd27a2ac5a53b92"><td class="memItemLeft" align="right" valign="top">svm_node * </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a16e1539ef1266ca9ddd27a2ac5a53b92">to_svm_node</a> (const torch::Tensor &sample)</td></tr>
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<tr class="memdesc:a16e1539ef1266ca9ddd27a2ac5a53b92"><td class="mdescLeft"> </td><td class="mdescRight">Convert single sample to libsvm format. <br /></td></tr>
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<tr class="separator:a16e1539ef1266ca9ddd27a2ac5a53b92"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a6bb2b4565b27df0db5f229dbd380795e" id="r_a6bb2b4565b27df0db5f229dbd380795e"><td class="memItemLeft" align="right" valign="top">feature_node * </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a6bb2b4565b27df0db5f229dbd380795e">to_feature_node</a> (const torch::Tensor &sample)</td></tr>
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<tr class="memdesc:a6bb2b4565b27df0db5f229dbd380795e"><td class="mdescLeft"> </td><td class="mdescRight">Convert single sample to liblinear format. <br /></td></tr>
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<tr class="separator:a6bb2b4565b27df0db5f229dbd380795e"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ab3e800a5016a915e9912d5873bb48741" id="r_ab3e800a5016a915e9912d5873bb48741"><td class="memItemLeft" align="right" valign="top">torch::Tensor </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#ab3e800a5016a915e9912d5873bb48741">from_predictions</a> (const std::vector< double > &predictions)</td></tr>
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<tr class="memdesc:ab3e800a5016a915e9912d5873bb48741"><td class="mdescLeft"> </td><td class="mdescRight">Convert predictions back to PyTorch tensor. <br /></td></tr>
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<tr class="separator:ab3e800a5016a915e9912d5873bb48741"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a5460485675613c54596418af3d5057ff" id="r_a5460485675613c54596418af3d5057ff"><td class="memItemLeft" align="right" valign="top">torch::Tensor </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a5460485675613c54596418af3d5057ff">from_probabilities</a> (const std::vector< std::vector< double > > &probabilities)</td></tr>
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<tr class="memdesc:a5460485675613c54596418af3d5057ff"><td class="mdescLeft"> </td><td class="mdescRight">Convert probabilities back to PyTorch tensor. <br /></td></tr>
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<tr class="separator:a5460485675613c54596418af3d5057ff"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a503eba54e8bb1f370e04b6e24354a32f" id="r_a503eba54e8bb1f370e04b6e24354a32f"><td class="memItemLeft" align="right" valign="top">torch::Tensor </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a503eba54e8bb1f370e04b6e24354a32f">from_decision_values</a> (const std::vector< std::vector< double > > &decision_values)</td></tr>
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<tr class="memdesc:a503eba54e8bb1f370e04b6e24354a32f"><td class="mdescLeft"> </td><td class="mdescRight">Convert decision values back to PyTorch tensor. <br /></td></tr>
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<tr class="memitem:aa0615f3de29958b2c5229d349f2f60ce" id="r_aa0615f3de29958b2c5229d349f2f60ce"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#aa0615f3de29958b2c5229d349f2f60ce">validate_tensors</a> (const torch::Tensor &X, const torch::Tensor &y=torch::Tensor())</td></tr>
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<tr class="memdesc:aa0615f3de29958b2c5229d349f2f60ce"><td class="mdescLeft"> </td><td class="mdescRight">Validate input tensors. <br /></td></tr>
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<tr class="memitem:a26342a8cc8b943f099112040aa960ae6" id="r_a26342a8cc8b943f099112040aa960ae6"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a26342a8cc8b943f099112040aa960ae6">get_n_features</a> () const</td></tr>
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<tr class="memdesc:a26342a8cc8b943f099112040aa960ae6"><td class="mdescLeft"> </td><td class="mdescRight">Get number of features from last conversion. <br /></td></tr>
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<tr class="memitem:a16999ded27bc2d42d2ebd9551b00c1cb" id="r_a16999ded27bc2d42d2ebd9551b00c1cb"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a16999ded27bc2d42d2ebd9551b00c1cb">get_n_samples</a> () const</td></tr>
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<tr class="memdesc:a16999ded27bc2d42d2ebd9551b00c1cb"><td class="mdescLeft"> </td><td class="mdescRight">Get number of samples from last conversion. <br /></td></tr>
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<tr class="memitem:a46d12ba28c4c5bf6e0fad1122c621fa8" id="r_a46d12ba28c4c5bf6e0fad1122c621fa8"><td class="memItemLeft" align="right" valign="top"><a id="a46d12ba28c4c5bf6e0fad1122c621fa8" name="a46d12ba28c4c5bf6e0fad1122c621fa8"></a>
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void </td><td class="memItemRight" valign="bottom"><b>cleanup</b> ()</td></tr>
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<tr class="memdesc:a46d12ba28c4c5bf6e0fad1122c621fa8"><td class="mdescLeft"> </td><td class="mdescRight">Clean up all allocated memory. <br /></td></tr>
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<tr class="memitem:a9259322e54d2477478a684e99d8e557a" id="r_a9259322e54d2477478a684e99d8e557a"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a9259322e54d2477478a684e99d8e557a">set_sparse_threshold</a> (double threshold)</td></tr>
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<tr class="memdesc:a9259322e54d2477478a684e99d8e557a"><td class="mdescLeft"> </td><td class="mdescRight">Set sparse threshold (features with absolute value below this are ignored) <br /></td></tr>
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<tr class="memitem:a1905f60fef9ffd3a8e8e45e41395352d" id="r_a1905f60fef9ffd3a8e8e45e41395352d"><td class="memItemLeft" align="right" valign="top">double </td><td class="memItemRight" valign="bottom"><a class="el" href="classsvm__classifier_1_1DataConverter.html#a1905f60fef9ffd3a8e8e45e41395352d">get_sparse_threshold</a> () const</td></tr>
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<tr class="memdesc:a1905f60fef9ffd3a8e8e45e41395352d"><td class="mdescLeft"> </td><td class="mdescRight">Get sparse threshold. <br /></td></tr>
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</table>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
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<div class="textblock"><p>Data converter between libtorch tensors and SVM library formats. </p>
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<p>This class handles the conversion between PyTorch tensors and the data structures required by libsvm and liblinear libraries. It manages memory allocation and provides efficient conversion methods. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8hpp_source.html#l00023">23</a> of file <a class="el" href="data__converter_8hpp_source.html">data_converter.hpp</a>.</p>
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</div><h2 class="groupheader">Constructor & Destructor Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#a5874904555f26448ed5ae4cf6f370056">◆ </a></span>DataConverter()</h2>
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<td>(</td>
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<p>Default constructor. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00010">10</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<h2 class="memtitle"><span class="permalink"><a href="#ac3af2c9c03cffe2968f29147611e333d">◆ </a></span>~DataConverter()</h2>
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<td class="memname">svm_classifier::DataConverter::~DataConverter </td>
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<td>(</td>
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<p>Destructor - cleans up allocated memory. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00017">17</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<h2 class="groupheader">Member Function Documentation</h2>
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<a id="a46d12ba28c4c5bf6e0fad1122c621fa8" name="a46d12ba28c4c5bf6e0fad1122c621fa8"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#a46d12ba28c4c5bf6e0fad1122c621fa8">◆ </a></span>cleanup()</h2>
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<p>Clean up all allocated memory. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00198">198</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<h2 class="memtitle"><span class="permalink"><a href="#a503eba54e8bb1f370e04b6e24354a32f">◆ </a></span>from_decision_values() <span class="overload">[1/2]</span></h2>
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<td class="paramname"><em>decision_values</em></td><td>)</td>
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<p>Convert decision values back to PyTorch tensor. </p>
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<dl class="params"><dt>Parameters</dt><dd>
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<dl class="section return"><dt>Returns</dt><dd>PyTorch tensor with decision values </dd></dl>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00152">152</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<h2 class="memtitle"><span class="permalink"><a href="#a503eba54e8bb1f370e04b6e24354a32f">◆ </a></span>from_decision_values() <span class="overload">[2/2]</span></h2>
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<p>Convert decision values back to PyTorch tensor. </p>
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<dl class="params"><dt>Parameters</dt><dd>
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<dl class="section return"><dt>Returns</dt><dd>PyTorch tensor with decision values </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#ab3e800a5016a915e9912d5873bb48741">◆ </a></span>from_predictions() <span class="overload">[1/2]</span></h2>
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<p>Convert predictions back to PyTorch tensor. </p>
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<dl class="section return"><dt>Returns</dt><dd>PyTorch tensor with predictions </dd></dl>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00120">120</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<p>Convert predictions back to PyTorch tensor. </p>
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<p>Convert probabilities back to PyTorch tensor. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00132">132</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<p>Get number of features from last conversion. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8hpp_source.html#l00100">100</a> of file <a class="el" href="data__converter_8hpp_source.html">data_converter.hpp</a>.</p>
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<p>Get number of features from last conversion. </p>
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<dl class="section return"><dt>Returns</dt><dd>Number of features </dd></dl>
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<p class="definition">Definition at line <a class="el" href="kernel__parameters_8hpp_source.html#l00100">100</a> of file <a class="el" href="kernel__parameters_8hpp_source.html">kernel_parameters.hpp</a>.</p>
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<h2 class="memtitle"><span class="permalink"><a href="#a16999ded27bc2d42d2ebd9551b00c1cb">◆ </a></span>get_n_samples() <span class="overload">[1/2]</span></h2>
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<p>Get number of samples from last conversion. </p>
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<dl class="section return"><dt>Returns</dt><dd>Number of samples </dd></dl>
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<p class="definition">Definition at line <a class="el" href="data__converter_8hpp_source.html#l00106">106</a> of file <a class="el" href="data__converter_8hpp_source.html">data_converter.hpp</a>.</p>
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<p>Get number of samples from last conversion. </p>
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<p class="definition">Definition at line <a class="el" href="kernel__parameters_8hpp_source.html#l00106">106</a> of file <a class="el" href="kernel__parameters_8hpp_source.html">kernel_parameters.hpp</a>.</p>
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<h2 class="memtitle"><span class="permalink"><a href="#a1905f60fef9ffd3a8e8e45e41395352d">◆ </a></span>get_sparse_threshold() <span class="overload">[1/2]</span></h2>
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<p>Get sparse threshold. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8hpp_source.html#l00123">123</a> of file <a class="el" href="data__converter_8hpp_source.html">data_converter.hpp</a>.</p>
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<p>Get sparse threshold. </p>
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<p class="definition">Definition at line <a class="el" href="kernel__parameters_8hpp_source.html#l00123">123</a> of file <a class="el" href="kernel__parameters_8hpp_source.html">kernel_parameters.hpp</a>.</p>
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<h2 class="memtitle"><span class="permalink"><a href="#a9259322e54d2477478a684e99d8e557a">◆ </a></span>set_sparse_threshold() <span class="overload">[1/2]</span></h2>
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<p>Set sparse threshold (features with absolute value below this are ignored) </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8hpp_source.html#l00117">117</a> of file <a class="el" href="data__converter_8hpp_source.html">data_converter.hpp</a>.</p>
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<p>Set sparse threshold (features with absolute value below this are ignored) </p>
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<p class="definition">Definition at line <a class="el" href="kernel__parameters_8hpp_source.html#l00117">117</a> of file <a class="el" href="kernel__parameters_8hpp_source.html">kernel_parameters.hpp</a>.</p>
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<p>Convert single sample to liblinear format. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00110">110</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<p>Convert single sample to liblinear format. </p>
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<p>Convert PyTorch tensors to liblinear format. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00060">60</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<p>Convert single sample to libsvm format. </p>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00100">100</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<p>Convert single sample to libsvm format. </p>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramname">sample</td><td>Feature tensor of shape (n_features,) </td></tr>
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</table>
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</dd>
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</dl>
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<dl class="section return"><dt>Returns</dt><dd>Pointer to svm_node array </dd></dl>
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</div>
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</div>
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<a id="a66f446e4decfe47bbba37c789f03f729" name="a66f446e4decfe47bbba37c789f03f729"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#a66f446e4decfe47bbba37c789f03f729">◆ </a></span>to_svm_problem() <span class="overload">[1/2]</span></h2>
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<td class="memname">std::unique_ptr< svm_problem > svm_classifier::DataConverter::to_svm_problem </td>
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<td>(</td>
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<td class="paramtype">const torch::Tensor & </td>
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<td class="paramname"><em>X</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const torch::Tensor & </td>
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<td class="paramname"><em>y</em> = <code>torch::Tensor()</code> </td>
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<td></td>
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<td>)</td>
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</div><div class="memdoc">
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<p>Convert PyTorch tensors to libsvm format. </p>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramname">X</td><td>Feature tensor of shape (n_samples, n_features) </td></tr>
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<tr><td class="paramname">y</td><td>Target tensor of shape (n_samples,) - optional for prediction </td></tr>
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</table>
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</dd>
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</dl>
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<dl class="section return"><dt>Returns</dt><dd>Pointer to svm_problem structure </dd></dl>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00022">22</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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<a id="a66f446e4decfe47bbba37c789f03f729" name="a66f446e4decfe47bbba37c789f03f729"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#a66f446e4decfe47bbba37c789f03f729">◆ </a></span>to_svm_problem() <span class="overload">[2/2]</span></h2>
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<div class="memproto">
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<table class="memname">
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<td class="memname">std::unique_ptr< svm_problem > svm_classifier::DataConverter::to_svm_problem </td>
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<td>(</td>
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<td class="paramtype">const torch::Tensor & </td>
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<td class="paramname"><em>X</em>, </td>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const torch::Tensor & </td>
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<td class="paramname"><em>y</em> = <code>torch::Tensor()</code> </td>
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</tr>
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<tr>
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<td></td>
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<td>)</td>
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<td></td><td></td>
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</tr>
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</table>
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</div><div class="memdoc">
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<p>Convert PyTorch tensors to libsvm format. </p>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramname">X</td><td>Feature tensor of shape (n_samples, n_features) </td></tr>
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<tr><td class="paramname">y</td><td>Target tensor of shape (n_samples,) - optional for prediction </td></tr>
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</table>
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</dd>
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</dl>
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<dl class="section return"><dt>Returns</dt><dd>Pointer to svm_problem structure </dd></dl>
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</div>
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</div>
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<a id="aa0615f3de29958b2c5229d349f2f60ce" name="aa0615f3de29958b2c5229d349f2f60ce"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#aa0615f3de29958b2c5229d349f2f60ce">◆ </a></span>validate_tensors() <span class="overload">[1/2]</span></h2>
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<td class="memname">void svm_classifier::DataConverter::validate_tensors </td>
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<td>(</td>
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<td class="paramtype">const torch::Tensor & </td>
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<td class="paramname"><em>X</em>, </td>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const torch::Tensor & </td>
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<td class="paramname"><em>y</em> = <code>torch::Tensor()</code> </td>
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</tr>
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<tr>
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<td></td>
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<td>)</td>
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<td></td><td></td>
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</div><div class="memdoc">
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<p>Validate input tensors. </p>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramname">X</td><td>Feature tensor </td></tr>
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<tr><td class="paramname">y</td><td>Target tensor (optional) </td></tr>
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</table>
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</dd>
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</dl>
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<dl class="exception"><dt>Exceptions</dt><dd>
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<table class="exception">
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<tr><td class="paramname">std::invalid_argument</td><td>if tensors are invalid </td></tr>
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</table>
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</dd>
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</dl>
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<p class="definition">Definition at line <a class="el" href="data__converter_8cpp_source.html#l00172">172</a> of file <a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a>.</p>
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</div>
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</div>
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<a id="aa0615f3de29958b2c5229d349f2f60ce" name="aa0615f3de29958b2c5229d349f2f60ce"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#aa0615f3de29958b2c5229d349f2f60ce">◆ </a></span>validate_tensors() <span class="overload">[2/2]</span></h2>
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<td class="memname">void svm_classifier::DataConverter::validate_tensors </td>
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<td>(</td>
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<td class="paramtype">const torch::Tensor & </td>
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<td class="paramname"><em>X</em>, </td>
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</tr>
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<tr>
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<td class="paramkey"></td>
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<td></td>
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<td class="paramtype">const torch::Tensor & </td>
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<td class="paramname"><em>y</em> = <code>torch::Tensor()</code> </td>
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</tr>
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<tr>
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<td></td>
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<td>)</td>
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<td></td><td></td>
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</tr>
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</table>
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</div><div class="memdoc">
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<p>Validate input tensors. </p>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramname">X</td><td>Feature tensor </td></tr>
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<tr><td class="paramname">y</td><td>Target tensor (optional) </td></tr>
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</table>
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</dd>
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</dl>
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<dl class="exception"><dt>Exceptions</dt><dd>
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<table class="exception">
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<tr><td class="paramname">std::invalid_argument</td><td>if tensors are invalid </td></tr>
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</table>
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</dd>
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</dl>
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</div>
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</div>
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<hr/>The documentation for this class was generated from the following files:<ul>
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<li>include/svm_classifier/<a class="el" href="data__converter_8hpp_source.html">data_converter.hpp</a></li>
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<li>include/svm_classifier/<a class="el" href="kernel__parameters_8hpp_source.html">kernel_parameters.hpp</a></li>
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<li>src/<a class="el" href="data__converter_8cpp_source.html">data_converter.cpp</a></li>
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</ul>
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