Pattern Recognition and Neural Networks
- Author: Brian D. Ripley, University of Oxford
- Date Published: January 2008
- availability: Available
- format: Paperback
- isbn: 9780521717700
Paperback
Looking for an inspection copy?
This title is not currently available for inspection. However, if you are interested in the title for your course we can consider offering an inspection copy. To register your interest please contact asiamktg@cambridge.org providing details of the course you are teaching.
-
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.
Read more- The most reliable account of the subject available - now in paperback
- Unparalleled coverage with valuable insights into the theory and a wide range of applications
- Real case-studies, data sets and examples help build skills and understanding
Reviews & endorsements
'The combination of theory and examples makes this a unique and interesting book.' A. Gelman, Journal of the International Statistical Institute
See more reviews'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
'… 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 Education Supplement
'... 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 valuable reference for engineers and science researchers.' Optics and Photonics News
Customer reviews
Not yet reviewed
Be the first to review
Review was not posted due to profanity
×Product details
- Date Published: January 2008
- format: Paperback
- isbn: 9780521717700
- length: 416 pages
- dimensions: 244 x 189 x 19 mm
- weight: 0.88kg
- contains: 41 b/w illus.
- availability: Available
Table of Contents
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.-
Resources for
Pattern Recognition and Neural Networks
Brian D. Ripley
General Resources
Find resources associated with this title
Type Name Unlocked * Format Size Showing of
This title is supported by one or more locked resources. Access to locked resources is granted exclusively by Cambridge University Press to lecturers whose faculty status has been verified. To gain access to locked resources, lecturers should sign in to or register for a Cambridge user account.
Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other lecturers may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.
Supplementary resources are subject to copyright. Lecturers are permitted to view, print or download these resources for use in their teaching, but may not change them or use them for commercial gain.
If you are having problems accessing these resources please contact lecturers@cambridge.org.
Related Books
also by this author
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email lecturers@cambridge.org
Register Sign in» Proceed
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.
Continue ×Are you sure you want to delete your account?
This cannot be undone.
Thank you for your feedback which will help us improve our service.
If you requested a response, we will make sure to get back to you shortly.
×