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Combining Pattern Classifiers
Hardcover
Technology & EngineeringDatabasesGeneral Computers
ISBN13: 9781118315231
Publisher: John Wiley & Sons
Published: Aug 29 2014
Pages: 384
Weight: 1.65
Height: 1.10 Width: 6.20 Depth: 9.30
Language: English
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.
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