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Combining Pattern Classifiers
Ludmila I. Kuncheva
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Description for Combining Pattern Classifiers
Hardcover. Combined classifiers, which are central to the ubiquitous performance of pattern recognition and machine learning, are generally considered more accurate than single classifiers. Num Pages: 384 pages, illustrations. BIC Classification: UYQP. Category: (P) Professional & Vocational. Dimension: 239 x 163 x 31. Weight in Grams: 762.
A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition
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® code and practice data sets throughout, Combining Pattern Classifiers includes:
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Format
Hardback
Publication date
2014
Publisher
John Wiley & Sons Inc United States
Number of pages
384
Condition
New
Number of Pages
384
Place of Publication
New York, United States
ISBN
9781118315231
SKU
V9781118315231
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Ludmila I. Kuncheva
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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