multisvm.m

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 cneuburg@fau.edu
%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 = 0;

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

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

result = u(k);
end