Bayesian Methods for Nonlinear Classification and Regression
Language: English
Published by Wiley, 2002
- Hardcover
- New
Seller: DeckleEdge LLC, Albuquerque, NM, U.S.A.DeckleEdge LLC
AbeBooks seller since September 28, 2023
Condition: New
£ 100.02
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Add to basketSeller Inventory # Shelfdream0471490369
- Title
- Bayesian Methods for Nonlinear Classification and Regression
- Author
- Denison, David G. T.; Holmes, Christopher C.; Mallick, Bani K.; Smith, Adrian F. M.
- Publisher
- Wiley
- Publication year
- 2002
- Condition
- new
- Binding
- hardcover
- Language
- English
- ISBN 10
- 0471490369
- ISBN 13
- 9780471490364
* Focuses on the problems of classification and regression using flexible, data-driven approaches.
* Demonstrates how Bayesian ideas can be used to improve existing statistical methods.
* Includes coverage of Bayesian additive models, decision trees, nearest-neighbour, wavelets, regression splines, and neural networks.
* Emphasis is placed on sound implementation of nonlinear models.
* Discusses medical, spatial, and economic applications.
* Includes problems at the end of most of the chapters.
* Supported by a web site featuring implementation code and data sets.
Primarily of interest to researchers of nonlinear statistical modelling, the book will also be suitable for graduate students of statistics. The book will benefit researchers involved inregression and classification modelling from electrical engineering, economics, machine learning and computer science.
"Synopsis" may belong to another edition of this title.
About the Author
David G. T. Denison and Christopher C. Holmes are the authors of Bayesian Methods for Nonlinear Classification and Regression, published by Wiley.
"About the title" may belong to another edition of this title.
DeckleEdge LLC
Albuquerque, NM, U.S.A.
AbeBooks seller since September 28, 2023
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