📄 gmmtrainparamset.html
字号:
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/REC-html40/loose.dtd"><html><head> <title>Description of gmmTrainParamSet</title> <meta name="keywords" content="gmmTrainParamSet"> <meta name="description" content="The following parameters are used for gmmTrain()"> <meta http-equiv="Content-Type" content="text/html; charset=big5"> <meta name="generator" content="m2html © 2003 Guillaume Flandin"> <meta name="robots" content="index, follow"> <link type="text/css" rel="stylesheet" href="../m2html.css"></head><body><a name="_top"></a><div><a href="../index.html">Home</a> > <a href="index.html">dcpr</a> > gmmTrainParamSet.m</div><!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png"> Master index</a></td><td align="right"><a href="index.html">Index for dcpr <img alt=">" border="0" src="../right.png"></a></td></tr></table>--><h1>gmmTrainParamSet</h1><h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>The following parameters are used for gmmTrain()</strong></div><h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>function gmmTrainParam=gmmTrainParamSet </strong></div><h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="fragment"><pre class="comment"> The following parameters are used for gmmTrain()</pre></div><!-- crossreference --><h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>This function calls:<ul style="list-style-image:url(../matlabicon.gif)"></ul>This function is called by:<ul style="list-style-image:url(../matlabicon.gif)"><li><a href="gmmGrowDemo.html" class="code" title="">gmmGrowDemo</a> Example of using gmmGrow.m for growing a GMM (gaussian mixture models).</li><li><a href="gmmInitParamSet.html" class="code" title="function gmmParam=gmmInitParamSet(data, gaussianNum, covType, gmmTrainParam);">gmmInitParamSet</a> gmmParamSet: Set a set of initial parameters for GMM</li><li><a href="gmmMleWrtGaussianNum.html" class="code" title="function [trainLp, testLp]=gmmMleWrtGaussianNum(trainData, testData, vecOfGaussianNum, covType, gmmTrainParam, plotOpt)">gmmMleWrtGaussianNum</a> </li><li><a href="gmmTrain.html" class="code" title="function [gmmParam, logProb] = gmmTrain(data, gaussianNumCovType, gmmTrainParam)">gmmTrain</a> gmmTrain: Parameter training for gaussian mixture model (GMM)</li><li><a href="gmmTrainDemo1d.html" class="code" title="">gmmTrainDemo1d</a> Example of using GMM (gaussian mixture model) for 1-D data</li><li><a href="gmmTrainDemo2dCovType01.html" class="code" title="">gmmTrainDemo2dCovType01</a> Animation of GMM training with covType=1 (isotropic) for 2D data</li><li><a href="gmmTrainDemo2dCovType02.html" class="code" title="">gmmTrainDemo2dCovType02</a> Animation of GMM training with covType=2 (diagonal cov. matrix) for 2D data</li><li><a href="gmmTrainDemo2dCovType03.html" class="code" title="">gmmTrainDemo2dCovType03</a> Animation of GMM training with covType=3 (full cov. matrix) for 2D data</li><li><a href="gmmTrainEvalWrtGaussianNum.html" class="code" title="function [gmmData, recogRate1, recogRate2, validMixNumIndex]=gmmTrainEvalWrtGaussianNum(DS, TS, vecOfMixNum, covType, gmmTrainParam)">gmmTrainEvalWrtGaussianNum</a> gmmTrainEvalWrtMixNum: GMM training and test, w.r.t. varying number of mixtures</li></ul><!-- crossreference --><h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="fragment"><pre>0001 <a name="_sub0" href="#_subfunctions" class="code">function gmmTrainParam=gmmTrainParamSet</a>0002 0003 <span class="comment">% The following parameters are used for gmmTrain()</span>0004 gmmTrainParam.dispOpt=0; <span class="comment">% Display info during training</span>0005 gmmTrainParam.plotOpt=0; <span class="comment">% Display rr with respect to mix numbers</span>0006 gmmTrainParam.useKmeans=1; <span class="comment">% Use kmeans to find the initial centers</span>0007 gmmTrainParam.maxIteration=20; <span class="comment">% Max. iteration</span>0008 gmmTrainParam.minImprove=eps; <span class="comment">% Min. improvement</span>0009 gmmTrainParam.minVariance=eps; <span class="comment">% Min. variance</span>0010 0011 <span class="comment">% The following parameters are used for gmmTrainEvalWrtGaussianNum()</span>0012 gmmTrainParam.useCenterSplitting=0; <span class="comment">% Use center splitting (Only if the no. of gaussians increases by the power of 2.)</span></pre></div><hr><address>Generated on Thu 30-Oct-2008 12:53:56 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/">m2html</a></strong> © 2003</address></body></html>⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -