Bayesian Nonparametrics via Neural Networks

Language: English

Published by Society for Industrial and Applied Mathematics,U.S., US, 2004

0898715636 / 9780898715637

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Bayesian Nonparametrics via Neural Networks is the first book to focus on neural networks in the context of nonparametric regression and classification, working within the Bayesian paradigm. It discusses neural networks in a statistical context, an approach in contrast to existing books, which tend to treat neural networks as a machine learning algorithm instead of a statistical model. Once this underlying statistical model is recognized, other standard statistical techniques can be applied to improve the model. The Bayesian approach allows better accounting for uncertainty. This book covers uncertainty in model choice and ways to deal with this issue, exploring ideas from statistics and machine learning. An analysis on the choice of prior and new noninformative priors is included, along with a substantial literature review. Written for statisticians using statistical terminology, this book will lead statisticians to an increased understanding of the neural network model and its applicability to real-world problems.

Seller Inventory # LU-9780898715637

Title
Bayesian Nonparametrics via Neural Networks
Author
Herbert K. H. Lee
Publisher
Society for Industrial and Applied Mathematics,U.S., US
Publication year
2004
Condition
New
Binding
Paperback
Language
English
ISBN 10
0898715636
ISBN 13
9780898715637
Item weight
203 grams
Dimensions
17.15 x 0.64 x 24.13 cm

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