- Hardcover: 680 pages
- Publisher: Wiley-Interscience; 2 edition (November 9, 2000)
- Language: English
- ISBN-10: 0471056693
- ISBN-13: 978-0471056690
- Product Dimensions: 7.3 x 1.2 x 10.3 inches
- Shipping Weight: 2.9 pounds (View shipping rates and policies)
- Average Customer Review: 3.9 out of 5 stars See all reviews (42 customer reviews)
- Amazon Best Sellers Rank: #293,004 in Books (See Top 100 in Books)
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Pattern Classification (Pt.1) 2nd Edition
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Frequently Bought Together
"…it provides a good introduction to the subject of Pattern Classification." (Journal of Classification, September 2007)
"…a fantastic book! The presentation...could not be better, and I recommend that future authors consider…this book as a role model." (Journal of Statistical Computation and Simulation, March 2006)
"...strongly recommended both as a professional reference and as a text for students..." (Technometrics, February 2002)
"...provides information needed to choose the most appropriate of 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 on Pattern Recognition can ignore this book, as it is the sort of book one 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 any serious student or worker in the field of pattern recognition." (Mathematical Reviews, Issue 2001k)
"...gives a systematic overview about the major topics in pattern recognition, based whenever possible on fundamental principles." (Zentralblatt MATH, Vol. 968, 2001/18)
"attractively presented and readable" (Journal of Classification, Vol.18, No.2 2001)
From the Back Cover
From the reviews . . .
"The first edition of this book, published 30 years ago by Duda and Hart, has been a defining book for the field of Pattern Recognition. Stork has done a superb job of updating the book. He has undertaken a monumental task of sifting through 30 years of material in a rapidly growing field and presented another snapshot of the field, determining what will be of importance for the next 30 years and incorporating it into this second edition. The style is easy to read as in the original book and the statistical, mathematical material comes alive with many new illustrations. The end result is harmonious, leading the reader through many new topics..."
–Sargur N. Srihari, PhD, Director, Center for Excellence in Document Analysis and Recognition, Distinguished Professor, Department of Computer Science and Engineering, SUNY at Buffalo
Practitioners developing or investigating pattern recognition systems in such diverse application areas as speech recognition, optical character recognition, image processing, or signal analysis, often face the difficult task of having to decide among a bewildering array of available techniques. This unique text/professional reference provides the information you need to choose the most appropriate method for a given class of problems, presenting an in-depth, systematic account of the major topics in pattern recognition today. A new edition of a classic work that helped define the field for over a quarter century, this practical book updates and expands the original work, focusing on pattern classification and the immense progress it has experienced in recent years. Special features include:
- Clear explanations of both classical and new methods, including neural networks, stochastic methods, genetic algorithms, and theory of learning
- Over 350 high-quality, two-color illustrations highlighting various concepts
- Numerous worked examples
- Pseudocode for pattern recognition algorithms
- Expanded problems, keyed specifically to the text
- Complete exercises, linked to the text
- Algorithms to explain specific pattern-recognition and learning techniques
- Historical remarks and important references at the end of chapters
- Appendices covering the necessary mathematical background
NOTE: Computer Manual in MATLAB to Accompany Pattern Classification, 2e users access toolbox via ftp://ftp.wiley.com/public/sci_tech_med/pattern_classification/ (Note: Visitors will require a password from the Manual to access.)
Top Customer Reviews
My reasons for disappointment with this book are as follows:
Given the 27 years that have elapsed since the publication of the first edition of the book, and the immense progress that has taken place in pattern recognition, machine learning, computational learning theory, grammar inference, statistical inference, algorithmic information theory, and related areas, the revisions and additions in the 2000 edition are essentially of a patchwork nature. In my opinion, they do not reflect the current understanding of the topic of pattern classification.
A disproportionate number of pages are devoted to topics like density estimation despite the fact that it has been well established in recent years, through the work of Vapnik and others, that when working with limited data, trying to solve the problem of pattern classification through density estimation (which turns out to be, in a well-defined sense of the term, a much harder problem than pattern classification) is rather futile. When modern techniques for learning pattern classifiers from limited data sets (e.g., support vector classifiers) are touched on in the book, the treatment is disappointingly superficial and in some cases, misleading.Read more ›
The appearance of the 2000 2nd edition led this writer to wonder if D&H could repeat with an offering as good as their first. In particular, would D&H have kept up with the considerable growth in methodology in the 1990s? Well, they have! With the addition of David Stork as third author, the second addition re-presents the basic theory, illustrated with some beautiful and complex figures, and knits it neatly with an exposition of neural networks, stochastic methods for posterior determination, nonmetric classification (tree search and string parsing), and clustering. Chapter 9 is a particularly interesting review of the recent machine learning research making the point that, absent knowledge of a problem's specific domain, no one classifier is better that any other. This chapter also reviews solutions to the problem of training on too-small samples including the Jackknife and bootstrap methods, and newer bagging and boosting algorithms popular in data mining applications.Read more ›
With this in mind the authors and their new coauthor David Stork go about the task of providing a revision. True to the goals of the original the authors undertake to describe pattern recognition under a variety of topics and with several available methods to cover each topic. Important new areas are covered and old but now deemed less significant are dropped. Advances in statistical computing and computing in general also dictate the topics. So although the authors are the same and the title is almost the same (note that scene analysis is dropped from the title) it is more like an entirely new book on the subject rthan a revision of the old. For a revision, I would expect to see mostly the same chapters with the same titles and only a few new chapters along with expansion of old chapters.
Although I view this as a new book, that is not necessarily bad. In fact it may be viewed as a strength of the book. It maintains the style and clarity of the original that we all loved but represents the state-of-the-art in pattern recognition at the beginning of the 21st Century.
The original had some very nice pictures. I liked some of them so much that I used them with permission in the section on classification error rate estimation in my bootstrap book. This edition goes much further with beautiful graphics including many nice three-dimensional color pictures like the one on the cover page.Read more ›
Most Recent Customer Reviews
The book seems to be bearly used at all. Great quality. Arrived on time as well. No complaints at allPublished 1 month ago by Amazon Customer
This is THE preeminent reference for pattern classification, and is essential in my workPublished 17 months ago by Carl Frost
the book is in a very good condition and
the content of it was very carefully written and include fundamental topics
Don't remember ordering this but I guess it was a good book for someone to use. Maybe it was a present for someone a long time ago.Published on December 24, 2013 by david