exrlpsvm.m

关于svm的例程

%
%
%   Examples of Robust linear program SVM
%
%


clear all
close all
tic

Napp = 3000; 
Nunl =10;
tic
sigma=0.4;
C=10;

[xapp,yapp,xtest,ytest, xtest1, xtest2]=dataset('gaussian',Napp,Nunl,sigma);
[xapp,xtest]=normalizemeanstd(xapp,xtest);






%load datavapnik.mat;
h1=plot(xapp(yapp==1,1),xapp(yapp==1,2),'+g'); hold on
set(h1,'LineWidth',2);
h2=plot(xapp(yapp==-1,1),xapp(yapp==-1,2),'xr'); 
set(h2,'LineWidth',2);
Napp=size(xapp,1);
Nbvar=size(xapp,2);



U=zeros(Nbvar+Nbvar+Napp+1,1); % w,s,eta et b
f=zeros(2*Nbvar+Napp+1,1);
f(Nbvar+1:2*Nbvar)=1;
f(2*Nbvar+1:2*Nbvar+Napp)=C;

xy= repmat(yapp,1,Nbvar).*xapp;
A=-[xy zeros(Napp,Nbvar) eye(Napp) -yapp];   % contraintes de biens class閟
A=[A; eye(Nbvar,Nbvar) -eye(Nbvar,Nbvar) zeros(Nbvar,Napp) zeros(Nbvar,1)];  
A=[A; -eye(Nbvar,Nbvar) -eye(Nbvar,Nbvar) zeros(Nbvar,Napp) zeros(Nbvar,1)];  

b=[-ones(Napp,1); zeros(2*Nbvar,1)];
lb=[-inf*ones(2*Nbvar,1);zeros(Napp,1);-inf];

 x=LINPROG(f,A,b,[],[],lb,[]);
 
 w=x(1:Nbvar,1);
 b=x(end);
 

 
[xtest1 xtest2]  = meshgrid([-1:.05:1]*3.5,[-1:0.05:1]*3); 
nn = length(xtest1); 
Xtest = [reshape(xtest1 ,nn*nn,1) reshape(xtest2 ,nn*nn,1)]; 

ypred= Xtest*w - b;
ypred = reshape(ypred,nn,nn); 




hold on
[cc,hh]=contour(xtest1,xtest2,ypred,[-1  0 1],'k');
clabel(cc,hh); 

%  kernel='poly';
%  kerneloption=1;
%  verbose=0;
%  lambda=1e-7;
%  
%  [xsup,w1,w0,pos,tps,alpha1] = svmclass(xapp,yapp,C,lambda,kernel,kerneloption,verbose); 
% ypred1 = svmval(Xtest,xsup,w1,w0,kernel,kerneloption,[ones(length(Xtest),1)]);
% ypred1 = reshape(ypred1,nn,nn);
% 
% 
% [cc,hh]=contour(xtest1,xtest2,ypred1,[-1  0 1],'r:');
% clabel(cc,hh);