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<html><head> <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1"> <title>Contents.m</title><link rel="stylesheet" type="text/css" href="../../stpr.css"></head><body><table border=0 width="100%" cellpadding=0 cellspacing=0><tr valign="baseline"><td valign="baseline" class="function"><b class="function">GREEDYAPPX</b><td valign="baseline" align="right" class="function"><a href="../../kernels/extraction/index.html" target="mdsdir"><img border = 0 src="../../up.gif"></a></table> <p><b>Kernel greedy data approximation.</b></p> <hr><div class='code'><code><span class=help></span><br><span class=help> <span class=help_field>Synopsis:</span></span><br><span class=help> [inx,Alpha,kercnt,mserr,maxerr]=...</span><br><span class=help> greedyappx(X,ker,arg,m,m2,mserr,maxerr,verb)</span><br><span class=help></span><br><span class=help> <span class=help_field>Description:</span></span><br><span class=help> This function aims to select a subset S of input data X such</span><br><span class=help> that the feature space representation of X can be well </span><br><span class=help> approximated by feature space representation of S.</span><br><span class=help> The feature represenation of data is by the use of</span><br><span class=help> specified kernel function.</span><br><span class=help></span><br><span class=help> The greedy algortihm is used to seletect the subset S. </span><br><span class=help> The algorithm iterates until on of the following stopping </span><br><span class=help> conditions is achieved:</span><br><span class=help> - number of vectors of S achieves m </span><br><span class=help> - maximal reconstruction error is less than maxerr </span><br><span class=help> - mean squared sum of reconstruction errors less than mserr. </span><br><span class=help> </span><br><span class=help> <span class=help_field>Input:</span></span><br><span class=help> X [dim x num_data] Input data.</span><br><span class=help> ker [string] Kernel identifier. See 'help kernel' for more info.</span><br><span class=help> arg [...] Argument of selected kernel.</span><br><span class=help> m [1x1] Maximal number of vector used for approximation.</span><br><span class=help> p [1x1] Depth of search for the best basis vector.</span><br><span class=help> mserr [1x1] Desired mean sum of squared reconstruction errors.</span><br><span class=help> maxerr [1x1] Desired maximal reconstruction error.</span><br><span class=help> verb [1x1] If 1 then infor about process is displayed.</span><br><span class=help></span><br><span class=help> <span class=help_field>Output:</span></span><br><span class=help> inx [1 x n] Indices of selected vector, i.e., S = X(:,inx).</span><br><span class=help> Alpha [m x m] Koefficient of the kernel projection of data on the</span><br><span class=help> found base vectors, i.e., z = Alpha*kernel(S,x,ker,arg).</span><br><span class=help> Z [m x num_data] Training data projected on the found base vectors.</span><br><span class=help> kercnt [1x1] Number of used kernel evaluations.</span><br><span class=help> MsErr [1 x m] Sum of squared reconstruction errors for corresponding</span><br><span class=help> number of base vectors.</span><br><span class=help> MaxErr [1 x m] Maximal squared reconstruction error for crresponding </span><br><span class=help></span><br><span class=help> <span class=also_field>See also </span><span class=also></span><br><span class=help><span class=also> <a href = "../../kernels/extraction/greedykpca.html" target="mdsbody">GREEDYKPCA</a>.</span><br><span class=help></span><br></code></div> <hr> <b>Source:</b> <a href= "../../kernels/extraction/list/greedyappx.html">greedyappx.m</a> <p><b class="info_field">About: </b> Statistical Pattern Recognition Toolbox<br> (C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac<br> <a href="http://www.cvut.cz">Czech Technical University Prague</a><br> <a href="http://www.feld.cvut.cz">Faculty of Electrical Engineering</a><br> <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a><br> <p><b class="info_field">Modifications: </b> <br> 10-dec-2004, VF, tmp(find(Errors<=0)) = -inf; added to evoid num errors.<br> 5-may-2004, VF<br> 13-mar-2004, VF<br> 10-mar-2004, VF<br> 9-mar-2004, addopted from greedyappx<br></body></html>?? 快捷鍵說明
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