By Nikolay Nikolaev,Hitoshi Iba
This publication promises theoretical and useful wisdom for constructing algorithms that infer linear and non-linear multivariate types, delivering a technique for inductive studying of polynomial neural community versions (PNN) from facts. The textual content emphasizes an prepared version identity strategy through which to find versions that generalize and are expecting good. The booklet additional allows the invention of polynomial types for time-series prediction.
Read Online 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)