Validation Error with trainbr is NaN

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gsourop
gsourop el 24 de Mzo. de 2017
Respondida: nazanin abz el 19 de Jun. de 2017
Hi everyone,
I would like to ask why do I get a vector of NaN values to the MSEval below when I apply the trainbr algorithm. However, when I apply the trainlm algorithm I get actual values.
a=randn(1,1000);
b= randn ( 1, 1000);
hiddenLayerSize= 1 ;
net = fitnet(hiddenLayerSize);
net.divideFcn = 'divideblock';
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 30/100;
net.divideParam.testRatio = 0/100;
net.trainFcn = 'trainbr';
net.trainParam.showWindow=false;
[net,tr] = train(net,a ,b);
outputs = net(a);
MSEval = tr.vperf
Thanks in advance.

Respuestas (1)

nazanin abz
nazanin abz el 19 de Jun. de 2017
it's not there by default anymore, you can use this command if you really need it. net.trainParam.max_fail = 6 However it's being said it's not necessary.

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