MATLAB: How to do a ROC analysis using Matlab build-in SVM (Not LibSVM)

rocsvm

Hi all,
Just wondering anyone knows how to do a ROC analysis using Matlab build-in SVM? This question has been asked by millions of times on the web, but no answer.
svmStruct                               = svmtrain(featureSelcted, groundTruthGroup, 'Kernel_Function', 'rbf', 'Method', 'QP');
svmClassified                           = svmclassify(svmStruct,featureSelcted);
% Predict resubstitution response of SVM classifier
SVMScore ???
% Fit probabilities for scores
[FPR, TPR, Thr, AUC, OPTROCPT]          = perfcurve(groundTruth(:,1), SVMScore(:,1), 1);
Essentially, we need a function to get the '*scores*' of the SVM classifier (SVMScore). Thanks!
A.

Best Answer

Well, there is an answer here http://www.mathworks.com/matlabcentral/answers/64475-does-anybody-have-expertise-with-matlab-svm-classifier, with a reference to another thread. I am collecting all the pieces in one place.
Assume your class labels are -1 and +1, assume that you have trained with 'autoscale' set to true by default, let svm be the struct for the trained SVM model, and let Xnew be the new data for which you need to compute the soft scores.
shift = svm.ScaleData.shift;
scale = svm.ScaleData.scaleFactor;
Xnew = bsxfun(@plus,Xnew,shift);
Xnew = bsxfun(@times,Xnew,scale);
sv = svm.SupportVectors;
alphaHat = svm.Alpha;
bias = svm.Bias;
kfun = svm.KernelFunction;
kfunargs = svm.KernelFunctionArgs;
f = kfun(sv,Xnew,kfunargs{:})'*alphaHat(:) + bias;
f = -f; % flip the sign to get the score for the +1 class
Then call perfcurve(true_labels,f,1).
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