By Nikolay Nikolaev,Hitoshi Iba
This booklet grants theoretical and useful wisdom for constructing algorithms that infer linear and non-linear multivariate versions, delivering a strategy for inductive studying of polynomial neural community versions (PNN) from information. The textual content emphasizes an prepared version identity method wherein to find types that generalize and expect good. The publication additional enables the invention of polynomial types for time-series prediction.
Read or Download Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation) PDF
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Extra resources for Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation)
Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation) by Nikolay Nikolaev,Hitoshi Iba