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📁 用matlab实现的统计模式识别工具箱
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<html><head>  <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1">  <title>tune_ocr.m</title><link rel="stylesheet" type="text/css" href="../../../m-syntax.css"></head><body><code><span class=h1>%&nbsp;TUNE_OCR&nbsp;Tunes&nbsp;SVM&nbsp;classifier&nbsp;for&nbsp;OCR&nbsp;problem.
</span><br><span class=help>%
</span><br><span class=help>%&nbsp;<span class=help_field>Description:</span></span><br><span class=help>%&nbsp;&nbsp;The&nbsp;following&nbsp;steps&nbsp;are&nbsp;performed:
</span><br><span class=help>%&nbsp;&nbsp;&nbsp;-&nbsp;Training&nbsp;set&nbsp;is&nbsp;created&nbsp;from&nbsp;data&nbsp;in&nbsp;directory&nbsp;ExamplesDir.
</span><br><span class=help>%&nbsp;&nbsp;&nbsp;-&nbsp;Multi-class&nbsp;SVM&nbsp;is&nbsp;trained&nbsp;for&nbsp;a&nbsp;set&nbsp;of&nbsp;arguments&nbsp;and&nbsp;
</span><br><span class=help>%&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;regularization&nbsp;constants.&nbsp;The&nbsp;best&nbsp;model&nbsp;is&nbsp;selected&nbsp;
</span><br><span class=help>%&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;based&nbsp;on&nbsp;the&nbsp;cross-validation&nbsp;error.
</span><br><span class=help>%&nbsp;&nbsp;&nbsp;&nbsp;
</span><br><hr><br><span class=help1>%&nbsp;<span class=help1_field>(c)</span>&nbsp;Statistical&nbsp;Pattern&nbsp;Recognition&nbsp;Toolbox,&nbsp;(C)&nbsp;1999-2003,
</span><br><span class=help1>%&nbsp;Written&nbsp;by&nbsp;Vojtech&nbsp;Franc&nbsp;and&nbsp;Vaclav&nbsp;Hlavac,
</span><br><span class=help1>%&nbsp;&lt;a&nbsp;href="http://www.cvut.cz"&gt;Czech&nbsp;Technical&nbsp;University&nbsp;Prague&lt;/a&gt;,
</span><br><span class=help1>%&nbsp;&lt;a&nbsp;href="http://www.feld.cvut.cz"&gt;Faculty&nbsp;of&nbsp;Electrical&nbsp;engineering&lt;/a&gt;,
</span><br><span class=help1>%&nbsp;&lt;a&nbsp;href="http://cmp.felk.cvut.cz"&gt;Center&nbsp;for&nbsp;Machine&nbsp;Perception&lt;/a&gt;
</span><br><br><span class=help1>%&nbsp;<span class=help1_field>Modifications:</span>
</span><br><span class=help1>%&nbsp;04-jun-2004,&nbsp;VF
</span><br><span class=help1>%&nbsp;09-sep-2003,&nbsp;VF
</span><br><br><hr>cd&nbsp;/home.dokt/xfrancv/work/new_stprtool/;
<br>stprpath;
<br>cd&nbsp;/home.dokt/xfrancv/work/new_stprtool/demos/ocr;
<br>
<br><span class=comment>%&nbsp;Setting&nbsp;
</span><br><span class=comment>%===================================
</span><br>ExamplesDir&nbsp;=&nbsp;<span class=quotes>'../../data/ocr_numerals/'</span>;&nbsp;&nbsp;<span class=comment>%&nbsp;input&nbsp;directory&nbsp;with&nbsp;exmaples
</span><br>OCRTuningFileName&nbsp;=&nbsp;<span class=quotes>'ocrtuning'</span>;&nbsp;&nbsp;<span class=comment>%&nbsp;output&nbsp;file&nbsp;with&nbsp;result&nbsp;of&nbsp;tuning
</span><br>
<br><span class=comment>%&nbsp;Model&nbsp;setting&nbsp;for&nbsp;multi-class&nbsp;SVM
</span><br>options.ker&nbsp;=&nbsp;<span class=quotes>'rbf'</span>;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=comment>%&nbsp;kernel&nbsp;type
</span><br>options.arg&nbsp;=&nbsp;[1&nbsp;2.5&nbsp;5&nbsp;7.5&nbsp;10]&nbsp;;&nbsp;&nbsp;<span class=comment>%&nbsp;kernel&nbsp;argument
</span><br>options.C&nbsp;=&nbsp;[inf];&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=comment>%&nbsp;regularization&nbsp;constant
</span><br>options.verb&nbsp;=&nbsp;1;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=comment>%&nbsp;display&nbsp;progress&nbsp;info
</span><br>options.solver&nbsp;=<span class=quotes>'oaosvm'</span>;
<br>options.num_fold&nbsp;=&nbsp;5;
<br>options.svm_options.solver&nbsp;=&nbsp;<span class=quotes>'svmlight'</span>;
<br>
<br><span class=comment>%&nbsp;Create&nbsp;training&nbsp;set&nbsp;
</span><br><span class=comment>%====================================
</span><br><span class=io>fprintf</span>(<span class=quotes>'Creating&nbsp;training&nbsp;set:\n'</span>);
<br>TrainingDataFile&nbsp;=&nbsp;[ExamplesDir&nbsp;<span class=quotes>'OcrTrndata.mat'</span>];
<br>mergesets(&nbsp;ExamplesDir,&nbsp;TrainingDataFile&nbsp;);
<br>data&nbsp;=&nbsp;load(TrainingDataFile&nbsp;);
<br>
<br><span class=comment>%&nbsp;Tuning&nbsp;SVM&nbsp;model
</span><br><span class=comment>%====================================
</span><br>
<br><span class=io>fprintf</span>(<span class=quotes>'Tuning&nbsp;multi-class&nbsp;SVM&nbsp;classifier.\n'</span>);
<br>[model,Error]&nbsp;=&nbsp;evalsvm(data,options);
<br>
<br><span class=io>fprintf</span>(<span class=quotes>'\nSaving&nbsp;results&nbsp;to:&nbsp;%s\n'</span>,OCRTuningFileName);
<br>save(OCRTuningFileName,<span class=quotes>'model'</span>,<span class=quotes>'Error'</span>,<span class=quotes>'options'</span>);
<br>
<br><span class=comment>%&nbsp;Visualization
</span><br><span class=comment>%====================================
</span><br><span class=comment>%figure;&nbsp;
</span><br><span class=comment>%load(OCRTuningFileName)
</span><br><span class=comment>%figure;&nbsp;mesh(options.arg,options.C,Errors);
</span><br><span class=comment>%hold&nbsp;on;&nbsp;xlabel('arg');&nbsp;ylabel('C');
</span><br><span class=comment>%figure;&nbsp;contour(options.arg,options.C,Errors);
</span><br><span class=comment>%hold&nbsp;on;&nbsp;xlabel('arg');&nbsp;ylabel('C');
</span><br>
<br><span class=comment>%&nbsp;EOF</span><br></code>

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