By Nikolay Nikolaev,Hitoshi Iba
This publication offers 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 info. The textual content emphasizes an equipped version identity method wherein to find types that generalize and are expecting good. The e-book extra enables the invention of polynomial versions 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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Additional resources for Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation)
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Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation) by Nikolay Nikolaev,Hitoshi Iba
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