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eBay-Artikelnr.:226732280970
Artikelmerkmale
- Artikelzustand
- Release Year
- 1996
- Book Title
- Pattern Recognition and Neural Networks
- ISBN
- 9780521460866
Über dieses Produkt
Product Identifiers
Publisher
Cambridge University Press
ISBN-10
0521460867
ISBN-13
9780521460866
eBay Product ID (ePID)
1039168
Product Key Features
Number of Pages
415 Pages
Language
English
Publication Name
Pattern Recognition and Neural Networks
Subject
Natural Language Processing, Neural Networks, Computer Vision & Pattern Recognition
Publication Year
1996
Type
Textbook
Subject Area
Computers
Format
Hardcover
Dimensions
Item Height
1.1 in
Item Weight
37.2 Oz
Item Length
10 in
Item Width
7.8 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
95-025223
Reviews
‘The combination of theory and examples makes this a unique and interesting book.’A. Gelman, Journal of the International Statistical Institute, The combination of theory and examples makes this a unique and interesting book. A. Gelman, Journal of the International Statistical Institute, ‘… a grand overview of both the theory and the practice of the field … of benefit to anyone who has an interest in a principled approach to statistical data analysis … will indeed provide an excellent reference for many years to come.’Stephen Roberts, The Times Higher Educational Supplement, 'The combination of theory and examples makes this a unique and interesting book.' A. Gelman, Journal of the International Statistical Institute, '... a grand overview of both the theory and the practice of the field ... of benefit to anyone who has an interest in a principled approach to statistical data analysis ... will indeed provide an excellent reference for many years to come.' Stephen Roberts, The Times Higher Educational Supplement, 'I can warmly recommend this book. Every researcher will benefit by the broadness of Ripley's view and the comprehensive bibliography.' Dee Denteneer, ITW Nieuws, ‘... an excellent text on the statistics of pattern classifiers and the application of neural network techniques … Ripley has managed … to produce an altogether accessible text …[it] will be rightly popular with newcomers to the area for its ability to present the mathematics of statistical pattern recognition and neural networks in an accessible format and engaging style.’Nature, "The combination of theory and examples makes this a unique and interesting book." International Statistical Institute Journal, '... an excellent text on the statistics of pattern classifiers and the application of neural network techniques ... Ripley has managed ... to produce an altogether accessible text ...[it] will be rightly popular with newcomers to the area for its ability to present the mathematics of statistical pattern recognition and neural networks in an accessible format and engaging style.' Nature, ‘I can warmly recommend this book. Every researcher will benefit by the broadness of Ripley’s view and the comprehensive bibliography.’Dee Denteneer, ITW Nieuws, "...an excellent text on the statistics of pattern classifiers and the application of neural network techniques...Ripley has managed...to produce an altogether accessible text...[it] will be rightly popular with newcomers to the area for its ability to present the mathematics of statistical pattern recognition and neural networks in an accessible format and engaging style." Nature, 'The combination of theory and examples makes this a unique and interesting book.'A. Gelman, Journal of the International Statistical Institute, '... an excellent text on the statistics of pattern classifiers and the application of neural network techniques … Ripley has managed … to produce an altogether accessible text …[it] will be rightly popular with newcomers to the area for its ability to present the mathematics of statistical pattern recognition and neural networks in an accessible format and engaging style.' Nature, '… a grand overview of both the theory and the practice of the field … of benefit to anyone who has an interest in a principled approach to statistical data analysis … will indeed provide an excellent reference for many years to come.' Stephen Roberts, The Times Higher Educational Supplement
Dewey Edition
20
Illustrated
Yes
Dewey Decimal
006.4
Table Of Content
1. Introduction and examples; 2. Statistical decision theory; 3. Linear discriminant analysis; 4. Flexible discriminants; 5. Feed-forward neural networks; 6. Non-parametric methods; 7. Tree-structured classifiers; 8. Belief networks; 9. Unsupervised methods; 10. Finding good pattern features; Appendix: statistical sidelines; Glossary; References; Author index; Subject index.
Synopsis
The clearest explanation of the statistical framework for pattern recognition and machine learning, now in paperback., Ripley brings together two crucial ideas in pattern recognition: statistical methods and machine learning via neural networks. He brings unifying principles to the fore, and reviews the state of the subject. Ripley also includes many examples to illustrate real problems in pattern recognition and how to overcome them., This 1996 book is a reliable account of the statistical framework for pattern recognition and machine learning. Valuable advice is included on both theory and applications, while case studies based on real data sets help readers develop their understanding. All data sets are available from www.stats.ox.ac.uk/~ripley/PRbook/, This 1996 book is a reliable account of the statistical framework for pattern recognition and machine learning. With unparalleled coverage and a wealth of case-studies this book gives valuable insight into both the theory and the enormously diverse applications (which can be found in remote sensing, astrophysics, engineering and medicine, for example). So that readers can develop their skills and understanding, many of the real data sets used in the book are available from the author's website: www.stats.ox.ac.uk/~ripley/PRbook/. For the same reason, many examples are included to illustrate real problems in pattern recognition. Unifying principles are highlighted, and the author gives an overview of the state of the subject, making the book valuable to experienced researchers in statistics, machine learning/artificial intelligence and engineering. The clear writing style means that the book is also a superb introduction for non-specialists.
LC Classification Number
QA76.87 .R56 1996
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