The best way to mitigate overtraining an overfit net is
MINIMIZE THE NUMBER OF HIDDEN NODES SUBJECT TO A MAXIMUM ALLOWED ERROR RATE.
The conventional I-H-O NN has I Input nodes, H Hidden nodes, O output nodes and Nw unknown weights where
Nw = (I+1)*H+(H+1)*O = (I+O+1)*H +1
With Ntrn training examples the total number of training equations is
To prevent overfitting: No. eq >= No. unknowns:
H <= Hmax <= Hub = (Ntrn*O-1)/(I+O+1)
I have posted zillions of examples in BOTH
comp.soft-sys.matlab and ANSWERS.
Search on "greg" and one or more of the following Ntrneq, Hmax, Hub
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