Selecting an optimal neural network

A relationship between optimal network design and statistical model identification is described. A derivative of Akaike's information criterion (AIC) is given. This modification yields an information statistic which can be used to select a best network for binary classification problems objectively. The technique can be extended to problems with an arbitrary number of classes.<
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