kernelSVDMSMEval.m

function RSLT = kernelSVDMSMEval(trainData, testData, nSubDim1, nSubDim2, nSigma, showFlag)
if ~exist('showFlag', 'var') || isempty(showFlag)
    showFlag = true;
else
    showFlag = false;
end

if ndims(testData) == 4
    testSet = size(testData, 3);
else
    testSet = 1;
end
nClass = size(trainData, 3);

RSLT = cell(size(nSubDim2, 2), size(nSubDim1, 2), size(nSigma, 2));
for i = 1:size(nSigma, 2)
    for j = 1:size(nSubDim1, 2)
        V1 = cvtKernelBasisVectorSVD(trainData, nSubDim1{j}, nSigma{i});
        for k = 1:size(nSubDim2, 2)
            V2 = cvtKernelBasisVectorSVD(testData, nSubDim2{k}, nSigma{i});
            sim = orzCanonicalAngles(V1, V2);
            RSLT{k, j, i} = OrzEval(sim(:, :, end, end), orzLabel(testSet, nClass));
            if showFlag == true
                fprintf('sigma: %0.3f, subdim1: %d, indim: %d, ER: %0.3f%%, EER: %0.3f%% \n', nSigma{i}, nSubDim1{j}, nSubDim2{k}, RSLT{k, j, i}.ER*100, RSLT{k, j, i}.EER*100);
            end
        end
    end
end
end