📄 minball.html
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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">MINBALL</b><td valign="baseline" align="right" class="function"><a href="../kernels/index.html" target="mdsdir"><img border = 0 src="../up.gif"></a></table> <p><b>Minimal enclosing ball in kernel feature space. </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> model = minball(X)</span><br><span class=help> model = minball(X,options)</span><br><span class=help></span><br><span class=help> <span class=help_field>Description:</span></span><br><span class=help> It computes center and radius of the minimal ball</span><br><span class=help> enclosing data X mapped into a feature space induced </span><br><span class=help> by a given kernel. The problem leads to a special instance </span><br><span class=help> of the Quadratic Programming task which is solved by the </span><br><span class=help> GMNP solver (see 'help gmnp').</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> options [struct] Control parameters:</span><br><span class=help> .ker [string] Kernel identifier (default 'linear'). See 'help kernel'.</span><br><span class=help> .arg [1 x nargs] Kernel arguments.</span><br><span class=help> .solver [string] Solver to be used (see 'help gmnp'); default 'imdm';</span><br><span class=help></span><br><span class=help> <span class=help_field>Output:</span></span><br><span class=help> model [struct] Center of the ball in the kernel feature space:</span><br><span class=help> .sv.X [dim x nsv] Data determining the center.</span><br><span class=help> .Alpha [nsv x 1] Data weights.</span><br><span class=help> .r [1x1] Radius of the minimal enclosing ball.</span><br><span class=help> .b [1x1] Squared norm of the center equal to Alpha'*K*Alpha.</span><br><span class=help> .options [struct] Copy of used options.</span><br><span class=help> .stat [struct] Statistics about optimization:</span><br><span class=help> .access [1x1] Number of requested columns of matrix H.</span><br><span class=help> .t [1x1] Number of iterations.</span><br><span class=help> .UB [1x1] Upper bound on the optimal value of criterion. </span><br><span class=help> .LB [1x1] Lower bound on the optimal value of criterion. </span><br><span class=help> .LB_History [1x(t+1)] LB with respect to iteration.</span><br><span class=help> .UB_History [1x(t+1)] UB with respect to iteration.</span><br><span class=help> .NA [1x1] Number of non-zero entries in solution.</span><br><span class=help></span><br><span class=help> <span class=help_field>Example:</span></span><br><span class=help> data = load('riply_trn');</span><br><span class=help> options = struct('ker','rbf','arg',1);</span><br><span class=help> model = minball(data.X,options);</span><br><span class=help> [Ax,Ay] = meshgrid(linspace(-5,5,100),linspace(-5,5,100));</span><br><span class=help> dist = kdist([Ax(:)';Ay(:)'],model);</span><br><span class=help> figure; hold on; </span><br><span class=help> ppatterns(data.X); ppatterns(model.sv.X,'ro',12);</span><br><span class=help> contour( Ax, Ay, reshape(dist,100,100),[model.r model.r]);</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/kdist.html" target="mdsbody">KDIST</a>.</span><br><span class=help></span><br></code></div> <hr> <b>Source:</b> <a href= "../kernels/list/minball.html">minball.m</a> <p><b class="info_field">About: </b> Statistical Pattern Recognition Toolbox<br> (C) 1999-2005, 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> 24-jan-2005, VF, Fast GMNP solver used.<br> 25-aug-2004, VF, added model.fun = 'kdist' and .diag_add changed to .mu <br> 16-may-2004, VF<br> 15-jun-2002, VF<br></body></html>
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