could anyone help me to compute the confusion matrix for training,validation and testing data set

code:
x = irisInputs;
t = irisTargets;
trainFcn = 'trainscg';  % Scaled conjugate gradient backpropagation.

% Create a Pattern Recognition Network
hiddenLayerSize = 10;
net = patternnet(hiddenLayerSize)

% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
% Train the Network
[net,tr] = train(net,x,t)

% Test the Network
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y);
tind = vec2ind(t);
yind = vec2ind(y);
percentErrors = sum(tind ~= yind)/numel(tind)
confusionmat(yind,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.