msvmclass2.m

很好用的统计模式识别工具箱

function [Ipred,mfpred] = msvmclass2(Xtst,Xtrn,Itrn,malpha,mbias,ker,arg,info)
% MSVMCLASS2 muli-class version of the SVM classifier.
%  [Ipred,mfpred] = msvmclass2(Xtst,Xtrn,Itrn,malpha,mbias,ker,arg,info)
%
% MSVMCLASS2 multiclass version of SVMCLASS (see 'help svmclass').
%
% Input:
%  Xtst [DxN] test points.
%  Xtrn [DxM] training points.
%  Itrn [1xM] labels of trainign points.
%  malpha [KxM] Lagrange multipliers.
%  mbias [Kx1] bias.
%  ker [string] kernel identifier (see help kernel).
%  arg [] arguments of given kernel (see help kernel).
%
% Output:
%  Itst [1xN] labels of test points (1,2).
%  mfpred [KxN] value of output function for each point (If greater or
%    equal to 0 then class is 1 else class is 2).
%
% See also SVMCLASS, SVM.
%

% Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac
% (c) Czech Technical University Prague, http://cmp.felk.cvut.cz
% Written Vojtech Franc (diploma thesis) 23.12.1999, 5.4.2000
% Modifications
% 19-September-2001, V. Franc, comments changed.

if nargin < 8,
  info=0;;
end
if nargin < 7,
  arg=[];
end

% get max class
maxclass=max(Itrn);

mfpred=zeros(maxclass,size(Xtst,2));


for class=1:maxclass,   
   
  if info,
    disp(sprintf('Class %d against the others', class ));
  end
  
   [tmp,mfpred(class,:)] = svmclass2(Xtst,Xtrn,multi2dicho(Itrn,class),...
      malpha(class,:),mbias(class),ker,arg,info);
end

[tmp,Ipred]=max(mfpred);


return;