mi-svm.rar_MI_MI-SVM_mi svm_mutual information

%mi-svm %data.mat is the matfile of the attributes from f1-f166; %Y.mat the frist column is every instance's bag label and the second column %is the instances number sequence of every bags. load data.mat; load Ylabel.mat patternlabel1=zeros(size(Ylabel,1),1); patternlabel2=Ylabel(:,1); while(patternlabel1~=patternlabel2) %need improve,"==" %caller C-svm programme,solve the W,b,and solution the pattern label F. %method select the best parameter by the libsvm, and then use the best %parameter in this code. so we can saving the time. C=input('please input the best C'); sigma=input('please input the best sigma'); ker = struct('type','gauss','width',sigma); X=data'; Y=patternlabel2'; patternlabel1=patternlabel2; options=optimset; options.largeScale='on'; options.MaxIter=4000; n=length(Y); H1=Y'*Y; H2=kernel(ker,X,X); H=(Y'*Y).*kernel(ker,X,X); f=-ones(n,1); A=[]; b=[]; Aeq=Y; beq=0; lb=zeros(n,1); ub=C*ones(n,1); a0=ones(n,1); [a,fval,eXitflag,output,lambda] = quadprog(H,f,A,b,Aeq,beq,lb,ub,a0,options); tmp=(a'.*Y)*kernel(ker,X,X); b=Y-tmp; b=mean(b); tmp=(a'.*Y)*kernel(ker,X,X); F=tmp+b; y=sign(F); i=1; while(Ylabel(i,1)==1) if(Ylabel(i,2)>=Ylabel(i+1,2)) m=Ylabel(i,2); bagf=F(1,i-m+1:i); bagy=y(1,i-m+1:i); if (sum(bagy)+m)/2==0 istar=find(max(bagf)); y(1,i-m+istar)=1; end end i=i+1; end patternlabel2=y'; end %find the best results W and b,then use the best result to solve the test %data and decise the test label. load testdata.mat load testbaglabel.mat testdata=testdata'; testtem=(a'.*Y)*kernel(ker,X,testdata); testy=sign(testtem+b); N=length(testbaglabel); j=0; baglabel=0; for h=1:(N-1) if testbaglabel(h)>=testbaglabel(h+1) j=j+1; numbag=testbaglabel(h); testbagy=testy(1,h-numbag+1:h); label=max(testbagy); baglabel(j)=label;% this is the label of bag; labelpattern(h-numbag+1:h,1)=label*ones(numbag,1);%this is the label of every instance. end ends totalbag=j; baglabel; testy; %the follow is the code of count the wright rate and discuss the %performance of the algorithm.