multisvm.m

function [itr] = multisvm( T,C,tst )
u=unique(C);
N=length(u);
c4=[];
c3=[];
j=1;
k=1;
if(N>2)
    itr=1;
    classes=0;
    cond=max(C)-min(C);
    while((classes~=1)&&(itr<=length(u))&& size(C,2)>1 && cond>0)
        c1=(C==u(itr));
        newClass=c1;
        svmStruct = svmtrain(T,newClass,'Kernel_Function','rbf','Method','QP');
        classes = svmclassify(svmStruct,tst);
        
       for i=1:size(newClass,2)
            if newClass(1,i)==0;
                c3(k,:)=T(i,:);
                k=k+1;
            end
        end
        T=c3;
        c3=[];
        k=1;
        
% This is the loop for reduction of group
        for i=1:size(newClass,2)
            if newClass(1,i)==0;
                c4(1,j)=C(1,i);
                j=j+1;
            end
        end
        C=c4;
        c4=[];
        j=1;
        
        cond=max(C)-min(C); 
                 


        if classes~=1
            itr=itr+1;
        end    
    end
end

end