Brief Description
This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.
Learn More about the Book
Pattern recognition has long been studied in relation to many different (and mainly unrelated) applications, such as remote sensing, computer vision, space research, and medical imaging. In this book Professor Ripley brings together two crucial ideas in pattern recognition; statistical methods and machine learning via neural networks. Unifying principles are brought to the fore, and the author gives an overview of the state of the subject. Many examples are included to illustrate real problems in pattern recognition and how to overcome them.This is a self-contained account, ideal both as an introduction for non-specialists readers, and also as a handbook for the more expert reader.
On the Back Cover
Known for his hype-free approach to neural networks, Brian Ripley here provides an excellent text on the statistics of pattern classifiers and the application of neural techniques...Ripley's text 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.
About the Author
Brian Ripley is the Professor of Applied Statistics at the University of Oxford and a member of the Department of Statistics as well as a Professorial Fellow of St. Peter's College.
Review Quotes
1. 'The combination of theory and examples makes this a unique and interesting book.' A. Gelman, Journal of the International Statistical Institute
2. '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
3. '... 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
4. ..."a valuable reference for engineers and science researchers." Optics & Photonics News
5. "The combination of theory and examples makes this a unique and interesting book." International Statistical Institute Journal
6. ..."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...Ýit¨ 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
7. .,."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
8. ., ."a valuable reference for engineers and science researchers." Optics & Photonics News
9. .,."a valuable reference for engineers and science researchers." Optics & Photonics News
10. ."..a valuable reference for engineers and science researchers." Optics & Photonics News
11. ."..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
12. ..".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
13. ..".a valuable reference for engineers and science researchers." Optics & Photonics News
