How do I identify nontrained members when using svm?

I downloaded the following file from matlab:

              function [result] = multisvm(TrainingSet,GroupTrain,TestSet)
              %Models a given training set with a corresponding group vector and 
              %classifies a given test set using an SVM classifier according to a 
              %one vs. all relation. 
              %
              %This code was written by Cody Neuburger [e-mail]
              %Florida Atlantic University, Florida USA
              %This code was adapted and cleaned from Anand Mishra's multisvm function
              %found at http://www.mathworks.com/matlabcentral/fileexchange/33170-multi-class-support-vector-machine/>

u=unique(GroupTrain);
numClasses=length(u);
result = zeros(length(TestSet(:,1)),1);

%build models
for k=1:numClasses
    %Vectorized statement that binarizes Group
    %where 1 is the current class and 0 is all other classes
    G1vAll=(GroupTrain==u(k));
    models(k) = svmtrain(TrainingSet,G1vAll);
end

%classify test cases
for j=1:size(TestSet,1)
    for k=1:numClasses
        if(svmclassify(models(k),TestSet(j,:))) 
            break;
        end
    end
    result(j) = k;
end

but when I send in data I did not train with it keeps giving a match for the test data. How am I supposed to test for people I did not train with? Thank you.

[prashanth r]

Hi,

can you please explain me how you build the model and the logic of classify code.

thank you.