Feedforward neurale network including minimum and maximum values??
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Hi, I am making a feed forward neurale network. The training set consist of approximately 4300 observations, with one input parameter (and one target). When I apply the neural network for simulations the network does not give any minimum or maximum values. How do I make the neural network include these values? The training set contains several observations of minimum and maximum values. I have tried different number of hidden neurons and different number of iterations, the problem is there for all the simulations.
All help are appreciated.
Best regards, Anne
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Greg Heath
2013-8-12
A typical objective of training is, given data ( DESIGN + NONDESIGN ) that can be considered to come from the same probability distribution, use
1. ONLY design (training + validation) data
2. As few hidden neurons as possible
to reduce the MSE of NONDESIGN (test) data below a specified threshold. For example
3. mse(ttst-ytst) < 0.01*mean(var(ttst',1))
This is usually attempted by trying to achieve a specified goal of MSEtrn proportional to mean(var(ttrn',1)) before MSEval reaches a minimum.
If you desire better fitting at extrema, use the errorWeight option of mse
help mse
doc mse
Hope this helps.
Thank you for formally accepting my answer
Greg
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