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<html><head> <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1"> <title>dualmean.m</title><link rel="stylesheet" type="text/css" href="../../m-syntax.css"></head><body><code><span class=defun_kw>function</span> <span class=defun_out>m</span>=<span class=defun_name>dualmean</span>(<span class=defun_in>varargin</span>)<br><span class=h1>% DUALMEAN Computes dual representation of mean vector.</span><br><span class=help>%</span><br><span class=help>% <span class=help_field>Synopsis:</span></span><br><span class=help>% m = dualmean(num_data)</span><br><span class=help>% m = dualmean(labels,y)</span><br><span class=help>%</span><br><span class=help>% <span class=help_field>Description:</span></span><br><span class=help>% This function computes a vector m which allows to express the mean</span><br><span class=help>% vector of data sample X [dim x num_data] in terms of dot products. </span><br><span class=help>%</span><br><span class=help>% m = dualmean(num_data) computes a vector m [num_data x 1] such that </span><br><span class=help>% mean(X,2) = X*m.</span><br><span class=help>%</span><br><span class=help>% m = dualmean(labels,y) computes a vector m [length(y) x 1] such that</span><br><span class=help>% mean(X(:,find(labels==y)),2) = X*m,</span><br><span class=help>%</span><br><span class=help>% where labels [1 x num_data] is a vector of data labels and y [1x1] </span><br><span class=help>% is a label od class which mean vector is to be computed.</span><br><span class=help>% </span><br><span class=help>% <span class=help_field>Example:</span></span><br><span class=help>% Unlabeled data:</span><br><span class=help>% data = load('riply_trn');</span><br><span class=help>% ma = mean( data.X, 2)</span><br><span class=help>% mb = data.X*dualmean(size(data.X,2))</span><br><span class=help>%</span><br><span class=help>% Labeled data:</span><br><span class=help>% data = load('riply_trn');</span><br><span class=help>% ma1 = mean( data.X(:,find(data.y==1)),2)</span><br><span class=help>% mb1 = data.X*dualmean(data.y,1)</span><br><span class=help>% ma2 = mean( data.X(:,find(data.y==2)),2)</span><br><span class=help>% mb2 = data.X*dualmean(data.y,2)</span><br><span class=help>%</span><br><span class=help>% See also </span><br><span class=help>% DUALCOV.</span><br><span class=help>%</span><br><hr><span class=help1>% <span class=help1_field>About:</span> Statistical Pattern Recognition Toolbox</span><br><span class=help1>% (C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac</span><br><span class=help1>% <a href="http://www.cvut.cz">Czech Technical University Prague</a></span><br><span class=help1>% <a href="http://www.feld.cvut.cz">Faculty of Electrical Engineering</a></span><br><span class=help1>% <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a></span><br><br><span class=help1>% <span class=help1_field>Modifications:</span></span><br><span class=help1>% 16-may-2004, VF</span><br><span class=help1>% 14-may-2004, VF</span><br><span class=help1>% 22-Jan-2003, VF</span><br><span class=help1>% 22-May-2001, V. Franc, created</span><br><br><hr><span class=keyword>if</span> <span class=stack>nargin</span> == 2,<br> <span class=comment>% labeled data</span><br> labels = <span class=stack>varargin</span>{1};<br> y = <span class=stack>varargin</span>{2};<br><br> num_data = length(labels);<br> m = zeros(num_data,1);<br> inx = find(labels==y);<br> m(inx) = ones(length(inx),1)/length(inx);<br><span class=keyword>else</span><br> <span class=comment>% unlabeled data</span><br> num_data = <span class=stack>varargin</span>{1};<br> m = ones(num_data,1)/num_data;<br><span class=keyword>end</span><br><br><span class=jump>return</span>;<br><span class=comment>% EOF</span><br></code>?? 快捷鍵說明
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