Bayesian Learning for Neural Networks

Name: Bayesian Learning for Neural Networks
Brand: Springer-Verlag New York Inc.
SKU: 9780387947242
Price: 935.81 RON
Availability: InStock

Autor: Radford M. Neal

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Editura: Springer-Verlag New York Inc.

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

Informații despre carte

Autor

Radford M. Neal

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

1996

Pagini

204

EAN

9780387947242

ISBN

0387947248

Enbook ID

01384136

Editura

Springer-Verlag New York Inc.

Greutate

326

Dimensiuni

233 x 158 x 16

Descriere completă

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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