?? kernelproj.html
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<html><head> <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1"> <title>kernelproj.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>out_data</span>=<span class=defun_name>kernelproj</span>(<span class=defun_in>in_data, model</span>)
<br><span class=h1>% KERNELPROJ Kernel projection.
</span><br><span class=help>%
</span><br><span class=help>% <span class=help_field>Synopsis:</span></span><br><span class=help>% Y = kernelproj(X, model)
</span><br><span class=help>% out_data = kernelproj(in_data, model)
</span><br><span class=help>%
</span><br><span class=help>% <span class=help_field>Description:</span></span><br><span class=help>% Y = kernelproj(X, model) this function maps input vectors
</span><br><span class=help>% X [dim x num_data] onto vectors Y [new_dim x num_data]
</span><br><span class=help>% using the kernel projection
</span><br><span class=help>%
</span><br><span class=help>% Y(:,i) = Alpha' * kernel(sv.X, X(:,i), ker, arg) + b
</span><br><span class=help>%
</span><br><span class=help>% where parameters of the projection are given in model:
</span><br><span class=help>% .Alpha [nsv x new_dim] Multipliers.
</span><br><span class=help>% .b [new_dim x 1] Bias.
</span><br><span class=help>% .sv.X [dim x nsv] Vectors.
</span><br><span class=help>% .options.ker [string] Kernel identifier.
</span><br><span class=help>% .options.arg [1 x narg] Kernel argument.
</span><br><span class=help>%
</span><br><span class=help>% out_data = kernelproj(in_data, model) assumes that in_data
</span><br><span class=help>% is a structure containing vectors X and labels y.
</span><br><span class=help>% The output structute out_data is constructed as
</span><br><span class=help>%
</span><br><span class=help>% out_data.X = kernelproj(in_data.X, model)
</span><br><span class=help>% out_data.y = in_data.y
</span><br><span class=help>%
</span><br><span class=help>% <span class=help_field>Example:</span></span><br><span class=help>% help kpca;
</span><br><span class=help>% help gda;
</span><br><span class=help>%
</span><br><span class=help>% See also
</span><br><span class=help>% GDA, KPCA, LINPROJ, KERNEL.
</span><br><span class=help>%
</span><br><hr><br><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>% 19-sep-2004, VF, core of the function rewritten to C
</span><br><span class=help1>% 14-may-2004, VF
</span><br><span class=help1>% 4-may-2004, VF
</span><br><br><hr><span class=keyword>if</span> isstruct(in_data)==1,
<br> out_data = in_data;
<br>
<br> <span class=keyword>if</span> ~isempty(model.Alpha) & isfield(model, <span class=quotes>'Alpha'</span>),
<br> out_data.X = kernelproj_mex(in_data.X, model.Alpha, model.b, ...
<br> model.sv.X, model.options.ker, model.options.arg);
<br> <span class=keyword>else</span>
<br> [dim,num_data]=size(in_data.X);
<br> out_data.X = model.b*ones(1,num_data);
<br> <span class=keyword>end</span>
<br>
<br><span class=keyword>else</span>
<br> <span class=keyword>if</span> ~isempty(model.Alpha) & isfield(model,<span class=quotes>'Alpha'</span>),
<br>
<br> out_data = kernelproj_mex(in_data, model.Alpha, model.b, ...
<br> model.sv.X, model.options.ker, model.options.arg);
<br> <span class=keyword>else</span>
<br> [dim,num_data]=size(in_data);
<br> out_data = model.b*ones(1,num_data);
<br> <span class=keyword>end</span>
<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(shuō)明
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