📄 gmmtraindemo1d.html
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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/REC-html40/loose.dtd"><html><head> <title>Description of gmmTrainDemo1d</title> <meta name="keywords" content="gmmTrainDemo1d"> <meta name="description" content="Example of using GMM (gaussian mixture model) for 1-D data"> <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> > gmmTrainDemo1d.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>gmmTrainDemo1d</h1><h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>Example of using GMM (gaussian mixture model) for 1-D data</strong></div><h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>This is a script file. </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"> Example of using GMM (gaussian mixture model) for 1-D data</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)"><li><a href="dcData.html" class="code" title="function DS = dcdata(dataID)">dcData</a> DCDATA Test data sets for data clustering (no class label).</li><li><a href="gaussian.html" class="code" title="function out = gaussian(data, gParam);">gaussian</a> gaussian: Multi-dimensional Gaussian propability density function</li><li><a href="gmmEval.html" class="code" title="function [logProb, gaussianProb] = gmmEval(data, gmmParam);">gmmEval</a> gmmEval: Evaluation of a GMM (Gaussian mixture model)</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="gmmTrainParamSet.html" class="code" title="function gmmTrainParam=gmmTrainParamSet">gmmTrainParamSet</a> The following parameters are used for gmmTrain()</li></ul>This function is called by:<ul style="list-style-image:url(../matlabicon.gif)"></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 <span class="comment">% Example of using GMM (gaussian mixture model) for 1-D data</span>0002 0003 <span class="comment">% ====== ?e?X???????????]Histogram?^</span>0004 DS = <a href="dcData.html" class="code" title="function DS = dcdata(dataID)">dcData</a>(7); data = DS.input;0005 subplot(2,1,1);0006 binNum = 30;0007 hist(data, binNum);0008 xlabel(<span class="string">'Data values'</span>); ylabel(<span class="string">'Counts'</span>); title(<span class="string">'Data histogram'</span>);0009 colormap(summer);0010 <span class="comment">% ====== ?i?? GMM ⌨️ 快捷键说明
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