How to optimize neural networks for over-dispersed target data?
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I am training a feedforwardnet that ought to predict accident rates from traffic and road characteristics of a large number of road segments. The target data is highly over-dispersed (a lot of zeros, where no accidents occurred over the observed period). I guess that this might be one problem. Does anyone have experience in optimizing network parameters such as training algorithm, number of neurons, even net type? A couple of pointers would be much appreciated.
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Greg Heath
il 19 Mar 2015
Use a radial basis function net
help newrb
doc newrb
Also consider newrbe , newgrnn, newpnn, etc
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