Combining Pattern Classifiers: Methods and Algorithms / Edition 1

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Overview

Replete with case studies and real-world applications, this text will be of interest to academics and researchers in the field seeking both new classification tools and new uses for the old ones.
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Editorial Reviews

From the Publisher
The well written 'Combining Pattern Classifiers'…is all about how patterns are to be recognized and interpreted." (Journal of Statistical Computation and Simulation, March 2006)

"In a clear and straightforward manner, the author provides a much-needed road map through a multifaceted and often controversial subject…" (International Journal of General Systems, June 2005)

"The book is very interesting and is written on a high scientific level…" (Mathematical Reviews, 2006c)

"...a unique and perfect book for researchers and practitioners who want to get a grasp of this new exciting area." (Journal of Intelligent & Fuzzy Systems, Vol. 16, No. 2, 2005)

"...a well-written and timely book, the first of its kind...a welcome contribution to pattern recognition...I would keep this book in my library." (Technometrics, November 2005)

"…destined to become essential reading…" (Zentralblatt MATH, Vol. 1066 (17), 2005)

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Product Details

  • ISBN-13: 9780471210788
  • Publisher: Wiley
  • Publication date: 7/1/2004
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 376
  • Product dimensions: 6.48 (w) x 9.47 (h) x 1.09 (d)

Meet the Author

Ludmila Kuncheva is a Professor of Computer Science at Bangor University, United Kingdom. She has received two IEEE Best Paper awards. In 2012, Dr. Kuncheva was awarded a Fellowship to the International Association for Pattern Recognition (IAPR) for her contributions to multiple classifier systems.

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Table of Contents

1 Fundamentals of pattern recognition 1
2 Base classifiers 45
3 Multiple classifier systems 101
4 Fusion of label outputs 111
5 Fusion of continuous-valued outputs 151
6 Classifier selection 189
7 Bagging and boosting 203
8 Miscellanea 237
9 Theoretical views and results 267
10 Diversity in classifier ensembles 295
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