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Pattern Classification, Second Edition: 1 (A Wiley-Interscience publication) (Hardcover)

by Richard O. Duda (Author), Peter E. Hart (Author), David G. Stork (Author, Editor) "Bayesian decision theory is a fundamental statistical approach to the problem of pattern classification ..." (more)

5.0 out of 5 stars See all reviews (1 customer review)

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This item: Pattern Classification, Second Edition: 1 (A Wiley-Interscience publication) by Richard O. Duda
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Computer Manual in MATLAB to Accompany Pattern Classification by David G. Stork
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Pattern Recognition and Machine Learning (Information Science and Statistics) (Information Science and Statistics) by Christopher M. Bishop
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Product details

Hardcover: 654 pages
Publisher: John Wiley & Sons Inc; 2Rev Ed edition (21 Nov 2001)
Language English
ISBN-10: 0471056693
ISBN-13: 978-0471056690
Product Dimensions: 25.8 x 18.2 x 3.2 cm

Average Customer Review: 5.0 out of 5 stars See all reviews (1 customer review)

Amazon.co.uk Sales Rank: 305,603 in Books (See Bestsellers in Books)
Popular in this category:
#43 in Books > Science & Nature > Engineering & Technology > Electronics & Communications Engineering > Electronics Engineering > Digital Electronics

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Product Description

Review

"…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)

Review

"...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)

"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)

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Inside This Book (Learn More)

First Sentence
Bayesian decision theory is a fundamental statistical approach to the problem of pattern classification. Read the first page

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	60% buy the item featured on this page: Pattern Classification, Second Edition: 1 (A Wiley-Interscience publication) 5.0 out of 5 stars (1) �93.53
	16% buy Pattern Recognition and Machine Learning (Information Science and Statistics) (Information Science and Statistics) 4.3 out of 5 stars (7) �48.44
	10% buy The Elements of Statistical Learning (Springer Series in Statistics) 5.0 out of 5 stars (1) �51.88
	8% buy Pattern Classification: WITH Computer Manual, 2r.e. �104.50

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2 of 2 people found the following review helpful:

5.0 out of 5 stars A must read.., 13 Jul 2007

By	Anthony Brew (Dublin, Ireland) - See all my reviews (REAL NAME)

I find this book extremely well written, for me I managed to get though a degree in Maths without doing any Statistics and I have found this a fantastic introduction to the area but also moving on to very interesting topics. What I really like is that the explanations and proofs are thorough and do not hand wave, but it's also possible to get the bigger picture just skimming though. When you get over bogged down in the proof and theory and the hands wave over your head in comes the power punch of this book, well prepared well laid out examples. In my opinion a damn good buy. I intend to read cover to cover and back again.

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