The training algorithm does not estimate weights using validation or test data.
data = design + test;
design = train + val
train: Estimates weights and biases
val : Stops training when performance on the non-training val data is optimized
test : Obtains an UNBIASED estimate of performance on unseen non-training data
You should be able to train with any combination of val and test data. Test data does not affect training. However val data provides one of several stopping options that is explicitly designed to prevent poor performance on non-training data.
Regardless of the combination used when training, the net can be saved and used on unseen data
save net
delete net
load net
ynew = net(xnew)
Hope this helps
Thank you for formally accepting my answer
Greg .
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