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Combining Pattern Classifiers: Methods and Algorithms Revised Edition
Contributor(s): Kuncheva, Ludmila I. (Author)
ISBN: 1118315235     ISBN-13: 9781118315231
Publisher: Wiley
OUR PRICE:   $121.55  
Product Type: Hardcover - Other Formats
Published: September 2014
Qty:
Additional Information
BISAC Categories:
- Technology & Engineering | Imaging Systems
- Computers | Computer Vision & Pattern Recognition
- Computers | Databases - Data Mining
Dewey: 006.4
LCCN: 2014014214
Physical Information: 1.1" H x 6.2" W x 9.3" (1.65 lbs) 384 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition

The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004. Dr. Kuncheva has plucked from the rich landscape of recent classifier ensemble literature the topics, methods, and algorithms that will guide the reader toward a deeper understanding of the fundamentals, design, and applications of classifier ensemble methods.

Thoroughly updated, with MATLAB(R) code and practice data sets throughout, Combining Pattern Classifiers includes:

  • Coverage of Bayes decision theory and experimental comparison of classifiers
  • Essential ensemble methods such as Bagging, Random forest, AdaBoost, Random subspace, Rotation forest, Random oracle, and Error Correcting Output Code, among others
  • Chapters on classifier selection, diversity, and ensemble feature selection

With firm grounding in the fundamentals of pattern recognition, and featuring more than 140 illustrations, Combining Pattern Classifiers, Second Edition is a valuable reference for postgraduate students, researchers, and practitioners in computing and engineering.