Why do i have NAN values in the confusion matrix only in the validation test?

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afef
afef 2017-6-27
评论： Ismail Cem Tüzün 2023-2-20
I wanted to create neural network for binary classification for dataset with input matrix with size [9 981] and output matrix [1 981]and this is the code that i used
rng('default');
inputs = patientInputs;
targets = patientTargets;
x = mapminmax(inputs);
t=targets;
trainFcn = 'trainbr';
% Create a Pattern Recognition Network
hiddenLayerSize =10;
net = patternnet(hiddenLayerSize,trainFcn);
net.divideFcn = 'dividerand'; % Divide data randomly
net.divideMode = 'sample'; % Divide up every sample
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
net.performFcn = 'mse';
% Choose Plot Functions
% For a list of all plot functions type: help nnplot
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ...
'plotconfusion', 'plotroc'};
% Train the Network
net= configure(net,x,t);
[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);
% Recalculate Training, Validation and Test Performance
trainTargets = t .* tr.trainMask{1};
valTargets = t .* tr.valMask{1};
testTargets = t .* tr.testMask{1};
trainPerformance = perform(net,trainTargets,y)
valPerformance = perform(net,valTargets,y)
testPerformance = perform(net,testTargets,y)
% View the Network
view(net)
At first i used the default trainFcn 'trainscg' then i tried to use 'trainbr' the accuracy improved but i got NAN values in the confusion matrix only in the validation test as you can see it here
Can anyone help me please?

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采纳的回答

Greg Heath
Greg Heath 2017-6-28
MATLAB doesn't allow a validation set for trainbr because they think it isn't necessary for generalization.
Although they are correct, I have found in the literature that using BOTH trainbr and a validation set is better in most cases.
Although you cannot force trainbr to have validation set, I think you can work around it using trainlm and/or trainscg with regularization.
Hope this helps
Thank you for formally accepting my answer
Greg
PS: I don't remember details.
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muhammed shames
muhammed shames 2018-11-5
Hello sir can you explain me how you got rid of that NaN values ? Ive been working on it but it didnt work by just setting the max fail to 6 !
Ismail Cem Tüzün
Ismail Cem Tüzün 2023-2-20
when I set max fail to 6 even 10, it worked. I also re-assigned my epoch number. May be it also affected the system, not sure. Thanks for the information, btw

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