Bayesian Learning for Neural Networks

Name: Bayesian Learning for Neural Networks
Brand: Springer-Verlag New York Inc.
SKU: 9780387947242
Price: 3882 CZK
Availability: InStock

Autor: Radford M. Neal

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer-Verlag New York Inc.

Dostupnost: Skladem u dodavatele

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Artificial "neural networks" are widely used as flexible models for classification and regression ap...

Informace o knize

Autor

Radford M. Neal

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

1996

Stránek

204

EAN

9780387947242

ISBN

0387947248

Enbook ID

01384136

Vydavatel

Springer-Verlag New York Inc.

Hmotnost

326

Rozměry

233 x 158 x 16

Kompletní popis

Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional training methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. A practical implementation of Bayesian neural network learning using Markov chain Monte Carlo methods is also described, and software for it is freely available over the Internet. Presupposing only basic knowledge of probability and statistics, this book should be of interest to researchers in statistics, engineering, and artificial intelligence.

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Bayesian Learning for Neural Networks

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