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Pattern Classification (2nd Edition) | 
 enlarge | Authors: Richard O. Duda, Peter E. Hart, David G. Stork
Publisher: Wiley-Interscience
Category: Book
List Price: $140.00
Buy New: $57.99
You Save: $82.01 (59%)
New (29) Used (18) from $57.99
Avg. Customer Rating:  26 reviews
Sales Rank: 43315
Media: Hardcover
Edition: 2
Number Of Items: 1
Pages: 654
Shipping Weight (lbs): 2.9
Dimensions (in): 10.2 x 7.2 x 1.3
ISBN: 0471056693
Dewey Decimal Number: 006.4
EAN: 9780471056690
ASIN: 0471056693
Publication Date: October 2000
Availability: Usually ships in 1-2 business days
Shipping: International shipping available
Condition: Brand New. International Edition. Softcover. Paper quality may be inferior but content is the same.
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| Editorial Reviews:
Product Description
The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
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| Customer Reviews: Read 21 more reviews...
 Terrible Problems April 9, 2008
2 out of 2 found this review helpful
I am not sure how this book gets consistently high marks. I am using this text for a graduate level course. While it does a decent job covering most of the topics, it has some glaring flaws.
For one the Homework Problems it provides are not really representative of what you're learning in the text. Almost all of the problems revolve around proofs, as opposed to using the concepts in practice. You can seemingly have a good grasp on the material, yet spend hours trying to solve each of the problems they provide for that particular section. My entire class has complained, and even my professor has admitted that even he isn't sure sometimes how they expect you to solve some of the problems.
Secondly, there are very few example problems demonstrated in the text, so the reader doesn't really get to see the concepts in action so to speak.
Also, there is a typo or error on almost every other page, sometimes even on important formulas.
Overall, I'd have to think there are better books out there. If this truly is "the best there is" as some reviewers claim, God help the field of Pattern Recognition.
 excellent revision of a classical text on statistical pattern recognition January 24, 2008
30 out of 30 found this review helpful
The 1973 book by Duda and Hart was a classic. It surveyed the literature on pattern classification and scene analysis and provided the practitioner with wonderful insight and exposition of the subject. In the intervening 28 years the field has exploded and there has been an enormous increase in technical approaches and applications.
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.
The standard classical material is covered in the first five chapters with new material included (e.g. the EM algorithm and hidden markov models in Chapter 3). Chapter 6 covers multilayer neural networks (a totally new area). Nonmetric methods including decision trees and the CART methodology are covered in Chapter 8. Each chapter has a large number of relevant references and many homework exercises and computer exercises.
Chapter 9 is "Algorithm-Independent Machine Learning" and it includes the wonderful "No Free Lunch" theorem (Theorem 9.1), a discussion of the minimum desciption length principle, overfitting issues and Occam's razor, bias - variance tradeoffs,resampling method for estimation and classifier evaluation, and ideas about combining classifiers.
Chapter 10 is on unsurpervised learning and clustering. In addition to the traditional techniques covered in the first edition the authors include the many advances in mixture models.
I was particularly interested in that part of Chapter 9. There is good coverage of the topics and they provide a number of good references. However, I was a bit disappointed with the cursory treatment of bootstrap estimation of classification accuracy (section 9.6.3 on pages 485 - 486). I particularly disagree with the simplistic statement "In practice, the high computational complexity of bootstrap estimation of classifier accuracy is rarely worth possible improvements in that estimate (Section 9.5.1)". On the other hand, the book is one of the first to cover the newer and also promising resampling approaches called "Bagging" and "Boosting" that these authors seem to favor.
Davison and Hinkley's bootstrap text is mentioned for its practical applications and guidance for bootstrapping. The authors overlook Shao and Tu which offers more in the way of guidance. Also my book provides some guidance for error rate estimation but is overlooked.
My book also illustrate the limitations of the bootstrap. Phil Good's book provides guidance and is mentioned by the authors. But his book is very superficial and overgeneralized with respect to guiding practitioners. For these reasons I held back my enthusiasm and only gave this text four stars.
Stick with the first edition November 19, 2007
5 out of 5 found this review helpful
I used the first edition of this book in a class on pattern recognition back in 1998. That old first edition did a great job of explaining the different aspects of pattern recognition as they were generally taught when the first edition came out in 1969. However, over the next 30 years the field expanded enough that a second edition was required. I purchased it, expecting an expanded version that went over the details as well as the first edition, and boy was I wrong. This second edition just glosses over the details of modern pattern classification techniques and doesn't show sufficient examples or even motivation for you to "get it". It's almost like the entire book is an introduction. I'm accustomed to the first chapter of a technical book being an overview that doesn't tell you much, but not the entire book. The only thing the second edition has to offer are slicker illustrations. My advice is find a copy of the first edition. It is very well put together. If you need additional material on subjects the first edition doesn't cover well, then go find more modern books specifically on those subjects. You may spend more money but at least you'll learn something.
Great product & service September 21, 2007
0 out of 4 found this review helpful
This was my first purchase from amazon and I was totally impressed by the quality of the product and the service! I would buy again from the same seller and recommend others to do the same.
 A Very Bad Sequel March 8, 2007
12 out of 14 found this review helpful
I have now used this book 3 times for a class. While the 1st edition did a nice job of covering the material in its time, the additions to in the 2nd addition are a disaster. What the book has going for it is that it at least lists the necessary material for such a course in the table of contents. However, all the additional material is poorly explained at best. The problem sets are too few and the ones that are included are generally weak.
I have tried to use this book, but after constant student complaints and my own difficulty with the text, I have finally concluded that the problem lies with the text and not with the users.
I think an indicator of problems was the large number of errors in the first printing; large here is an understatement. Even in later additions, the 4th, the size of the errata is huge. I think this is indicative of the authors' attention to detail and seriousness in preparation. I have found similar errors and ambiguities in the associate Computer Manual.
The bottom line is that this book has seen its final appearance in our curriculum. I would use any other text, even an older one.
There is simply not enough room or time to point out all the problems with this text. Do yourself a favor if considering this text for a class. Don't bother.
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