Neural Network Toolbox Turn off Early Stopping

Hi,

I need to make a training algorithm such as trainlm or traingd overfit. Therefore I want to turn off early stopping. The following is my code:

net = feedforwardnet(neurons,trainalgo);
net = init(net);

%net.trainParam.max_fail = max_fail;
net.divideFcn = 'dividerand';
net.divideParam.trainRatio=trainRatio;
net.divideParam.valRatio=valRatio;
net.divideParam.testRatio=testRatio;
net.trainParam.epochs = epochs;
net.trainParam.min_grad=0;

% Train network and retrieve mse's.
[net tr] = train(net, x, y);
trE = tr.perf; 
vE = tr.vperf;
tE = tr.tperf;

I want the min_grad to be irrelevant. Even if it's zero I still want it to continue to train until epoch 1000. How do I do that?

Thanks

Answer 1

[Greg Heath]

Set the training goal to 0

and

set the allowed no. of validation increases to inf.

Hope this helps.

Thank you for formally accepting my answer

Greg

Answer 2

[orlem lima dos santos]

hello there is no straightforward way to do this, but you can

1. set trainRatio = 1, valRatio=0 and testRatio=0 (this stops the validation checks).

2. set the training goal to 0.

3. set net.trainParam.min_grad=1e-100; (the gradient is never going to achieve 1e-100)

this only the only way to the training stop is when it achieves the maximum number of epochs (net.trainParam.epochs)

I hope it helps