I've read form Greg Heath:
Data = Design + Non-design
Design = Train(estimate weights) + Validation(Stop training when MSEval goes thru a minimum).
Non-design = Test(Obtain UNBIASED generalization estimate of performance on unseen non-design data).
I like to know why and how test results are calculated on unbiased net despite the fact that training is made on biased network and how to obtain the same results using :
output=net(input)
I must use :
net.biasConnect = [0; 0];
after training and before using net for new outputs?
There is a contradiction between training net and the changing made after?
What do you mean when you say in:
"The test set error is unbiased because it is completely independent of design (training and validation)." ?
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