# cswetenham/pmr

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 % Compute a random permutation of the frames % NFrames = NFrames; % Idx : 1 x NFrames Idx = randperm(NFrames); % RandSeq: [NFrames x NFeatures] RandSeq = sequence_X(Idx, :); NFolds = 7; FoldSize = NFrames/NFolds; Ms = [1 2 5 10 15 20 25]'; LLTrain = zeros(size(Ms)); LLTest = zeros(size(Ms)); for MIdx = 1:size(Ms) M = Ms(MIdx); LLTrainTot = 0; LLTestTot = 0; for V = 1:NFolds TestSet = RandSeq(1 : FoldSize, :); TrainSet = RandSeq(FoldSize + 1 : NFrames, :); RandSeq = circshift(RandSeq, 83); [W,Mu,DiagPsi,~] = fa(TrainSet, M, 50); LLTestTot = LLTestTot + fallikelihood(TestSet, W, DiagPsi, Mu); LLTrainTot = LLTrainTot + fallikelihood(TrainSet, W, DiagPsi, Mu); end % Compute the average across the NFolds runs LLTest(MIdx) = LLTestTot/NFolds; LLTrain(MIdx) = LLTrainTot/NFolds; end % We need to scale the log likelihoods by the number of instances in order % to make them comparable. LLTest = LLTest * NFolds; LLTrain = LLTrain * NFolds / (NFolds-1); figure; plot(Ms, LLTest, 'g'); hold on; plot(Ms, LLTrain, 'b'); writeFigurePDF('p3q5.pdf');
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