Pattern Classification
2nd Edition
Published on 9. November 2012
680 pages
978-1-118-58600-6 (ISBN)
Description
The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics.
An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.
Reviews / Votes
"...it provides a good introduction to the subject of PatternClassification." (Journal of Classification, September 2007) "...a fantastic book! The presentation...could not bebetter, and I recommend that future authors consider...thisbook as a role model." (Journal of Statistical Computation andSimulation, March 2006) "...strongly recommended both as a professional reference and asa text for students..." (Technometrics, February 2002) "...provides information needed to choose the most appropriateof the many available technique for a given class of problems."(SciTech Book News, Vol. 25, No. 2, June 2001) "I do not believe anybody wishing to teach or do serious work onPattern Recognition can ignore this book, as it is the sort of bookone wishes to find the time to read from cover to cover!"(Pattern Analysis & Applications Journal, 2001) "This book is the unique text/professional reference for anyserious student or worker in the field of pattern recognition."(Mathematical Reviews, Issue 2001k) "...gives a systematic overview about the major topics inpattern recognition, based whenever possible on fundamentalprinciples." (Zentralblatt MATH, Vol. 968, 2001/18) "attractively presented and readable" (Journal ofClassification, Vol.18, No.2 2001)More details
Other editions
Additional editions
Richard O. Duda | Peter E. Hart | David G. Stork
Pattern Classification
Book
11/2000
2nd Edition
Wiley
€181.50
Shipment within 10-20 days
Persons
RICHARD O. DUDA, PhD, is Professor in the Electrical EngineeringDepartment at San Jose State University, San Jose,California.
PETER E. HART, PhD, is Chief Executive Officer and President ofRicoh Innovations, Inc. in Menlo Park, California.
DAVID G. STORK, PhD, is Chief Scientist, also at Ricoh Innovations,Inc.
Content
Bayesian Decision Theory.
Maximum-Likelihood and Bayesian Parameter Estimation.
Nonparametric Techniques.
Linear Discriminant Functions.
Multilayer Neural Networks.
Stochastic Methods.
Nonmetric Methods.
Algorithm-Independent Machine Learning.
Unsupervised Learning and Clustering.
Appendix.
Index.
