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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 hclusteringDemo</title> <meta name="keywords" content="hclusteringDemo"> <meta name="description" content="LINKCLU Display the formation of hierarchical clustering step by step"> <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> > hclusteringDemo.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>hclusteringDemo</h1><h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>LINKCLU Display the formation of hierarchical clustering step by step</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 hClusteringDemo(pattern_mat, distance, level) </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"> LINKCLU Display the formation of hierarchical clustering step by step
Usage: hClusteringDemo(pattern_mat, distance, level)
pattern_mat: pattern matrix
distance: distance matrix of the pattern matrix
level: hierarchical clustering result of the patern matrix
Type "hclustdm" to see a demo of a step-by-step hierarchical clustering
(single-linkage) of 50 random patterns of dimensionality 2.
See also <a href="aggclust.html" class="code" title="function level = aggclust(distance, method)">AGGCLUST</a>, <a href="dendro.html" class="code" title="function dendro(level)">DENDRO</a>.</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="aggclust.html" class="code" title="function level = aggclust(distance, method)">aggclust</a> aggClust: Hierarchical (agglomerative) clustering</li><li><a href="dendro.html" class="code" title="function dendro(level)">dendro</a> DENDRO Dendrogrma plot for the result from hierarchical clustering.</li></ul>This function is called by:<ul style="list-style-image:url(../matlabicon.gif)"></ul><!-- crossreference --><h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><ul style="list-style-image:url(../matlabicon.gif)"><li><a href="#_sub1" class="code">function selfdemo</a></li></ul><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 hClusteringDemo(pattern_mat, distance, level)</a>0002 <span class="comment">% LINKCLU Display the formation of hierarchical clustering step by step</span>0003 <span class="comment">%</span>0004 <span class="comment">% Usage: hClusteringDemo(pattern_mat, distance, level)</span>0005 <span class="comment">% pattern_mat: pattern matrix</span>0006 <span class="comment">% distance: distance matrix of the pattern matrix</span>0007 <span class="comment">% level: hierarchical clustering result of the patern matrix</span>0008 <span class="comment">%</span>0009 <span class="comment">% Type "hclustdm" to see a demo of a step-by-step hierarchical clustering</span>0010 <span class="comment">% (single-linkage) of 50 random patterns of dimensionality 2.</span>0011 <span class="comment">%</span>0012 <span class="comment">% See also AGGCLUST, DENDRO.</span>0013 0014 <span class="comment">% Roger Jang, 19981027</span>0015 0016 <span class="comment">% Demo when no input arguments</span>0017 <span class="keyword">if</span> nargin == 0, <a href="#_sub1" class="code" title="subfunction selfdemo">selfdemo</a>; <span class="keyword">return</span>, <span class="keyword">end</span>0018 0019 plot(pattern_mat(:, 1), pattern_mat(:, 2), <span class="string">'bo'</span>);0020 axis equal;0021 axis square;0022 data_n = size(pattern_mat, 1);0023 <span class="keyword">for</span> i = 2:data_n,0024 <span class="keyword">if</span> i>=3, set(h, <span class="string">'color'</span>, <span class="string">'k'</span>); <span class="keyword">end</span>0025 [m, n] = find(distance==level(i).height);0026 h = line(pattern_mat(m,1), pattern_mat(m,2), <span class="string">'color'</span>, <span class="string">'r'</span>, <span class="string">'erase'</span>, <span class="string">'none'</span>);0027 drawnow;0028 <span class="comment">% fprintf('Press any key to form %g clusters ...\n', data_n-i+1); pause;</span>0029 pause(0.1);0030 <span class="keyword">end</span>0031 0032 <span class="comment">% ====== Self demo ======</span>0033 <a name="_sub1" href="#_subfunctions" class="code">function selfdemo</a>0034 data_n = 50;0035 dimension = 2;0036 points = rand(data_n, dimension);0037 0038 <span class="comment">% ====== data from fcmdemo.m</span>0039 data_n = 50;0040 k = 10;0041 c1 = [0.125 0.25];0042 data1 = randn(data_n, 2)/k + ones(data_n, 1)*c1;0043 c2 = [0.625 0.25];0044 data2 = randn(data_n, 2)/k + ones(data_n, 1)*c2;0045 c3 = [0.375 0.75];0046 data3 = randn(data_n, 2)/k + ones(data_n, 1)*c3;0047 c4 = [0.875 0.75];0048 data4 = randn(data_n, 2)/k + ones(data_n, 1)*c4;0049 data = [data1; data2; data3; data4];0050 index = (min(data')>0) & (max(data')<1);0051 data(find(index == 0), :) = [];0052 points = data;0053 data_n = size(points,1);0054 0055 0056 <span class="keyword">for</span> i = 1:data_n,0057 <span class="keyword">for</span> j = 1:data_n,0058 distance(i, j) = norm(points(i,:)-points(j,:));0059 <span class="keyword">end</span>0060 <span class="keyword">end</span>0061 0062 <span class="comment">% Diagonal elements should always be inf.</span>0063 <span class="keyword">for</span> i = 1:data_n, distance(i, i) = inf; <span class="keyword">end</span>0064 0065 method = <span class="string">'single'</span>;0066 <span class="comment">%method = 'complete';</span>0067 level = <a href="aggclust.html" class="code" title="function level = aggclust(distance, method)">aggclust</a>(distance, method);0068 0069 <span class="comment">% Plot heights w.r.t. levels</span>0070 <span class="comment">%figure;</span>0071 <span class="comment">%plot([level.height], 'r:o');</span>0072 <span class="comment">%xlabel('Level');</span>0073 <span class="comment">%ylabel('Height');</span>0074 <span class="comment">%title('Height vs. level');</span>0075 0076 <span class="comment">% Plot the dendrogram</span>0077 figure;0078 <a href="dendro.html" class="code" title="function dendro(level)">dendro</a>(level);0079 0080 figure;0081 plot([level.height], <span class="string">'r:o'</span>);0082 xlabel(<span class="string">'Level'</span>);0083 ylabel(<span class="string">'Height'</span>);0084 title(<span class="string">'Height vs. level'</span>);0085 0086 <span class="comment">% View the formation of clusters</span>0087 figure;0088 title(<span class="string">'Press any key to link clusters.'</span>);0089 feval(mfilename, points, distance, level);0090 title(<span class="string">'The whole data set has been linked to a single cluster!'</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
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