
Bayesian Nonparametrics Via Neural Networks
Herbert K. H. Lee(Author)
Society for Industrial and Applied Mathematics (SIAM) (Publisher)
Published on 1. June 2004
Book
Paperback/Softback
96 pages
978-0-89871-563-7 (ISBN)
Description
The first book to focus on neural networks in the context of nonparametric regression and classification, working within the Bayesian paradigm. Its goal is to demystify neural networks, putting them firmly in a statistical context rather than treating them as a black box.
More details
Language
English
Place of publication
Philadelphia
United States
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 228 mm
Width: 152 mm
Thickness: 7 mm
Weight
204 gr
ISBN-13
978-0-89871-563-7 (9780898715637)
Schweitzer Classification
Content
- Preface
- Chapter 1: Introduction
- Chapter 2: Nonparametric Models
- Chapter 3: Priors for Neural Networks
- Chapter 4: Building A Model
- Chapter 5: Conclusions
- Appendix A: Reference Prior Derivation
- Glossary
- Bibliography
- Index.