x = irisInputs;
t = irisTargets;
trainFcn = 'trainscg';
hiddenLayerSize = 10;
net = patternnet(hiddenLayerSize)
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
[net,tr] = train(net,x,t)
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y);
tind = vec2ind(t);
yind = vec2ind(y);
percentErrors = sum(tind ~= yind)/numel(tind)
The above code executes and gives me the result of overall confusion matrix.
but I want to compute the confusion matrix of training,validation and testing data set separately.
Could anyone please help me on it.