confusionMatrix

  [cf,allcf] = confusionMatrix(cv)

0001 function [cf,allcf] = confusionMatrix(cv)
0002 %  [cf,allcf] = confusionMatrix(cv)
0003 
0004 nTestTrials = length(cv.testResults);
0005 nTasks = size(cv.classes,1);
0006 
0007 sumcf = 0;
0008 for ttrial = 1:nTestTrials
0009   classes = cv.testResults{ttrial}{5};
0010   nPerTask = round(length(classes)/nTasks);
0011   if nPerTask*nTasks ~= length(classes)
0012     error('Not even number of samples per class');
0013   end
0014   classes = reshape(classes,nPerTask,nTasks);
0015   onecf = hist(classes,nTasks);  %true in cols, predicted in rows
0016   onecf = onecf ./ (repmat(sum(onecf),nTasks,1)) * 100;
0017   allcf{ttrial} = onecf;
0018   sumcf = sumcf + onecf;
0019 end
0020 cf = sumcf / nTestTrials;
0021 
0022 %printConfusionMatrix(cf);