Adaptive Learning of Polynomial Networks : Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation)

The main claim is that the model identification process involves several equally important steps: finding the model structure, estimating the model weight parameters, and tuning these weights with respect to the adopted assumptions about the underlying data distrib­ ution.