Combining Pattern Classifiers

Combining Pattern Classifiers

Author: Ludmila I. Kuncheva

Publisher: John Wiley & Sons

ISBN: 9781118315231

Category: Technology & Engineering

Page: 384

View: 201

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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: 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.
Combining Pattern Classifiers
Language: en
Pages: 384
Authors: Ludmila I. Kuncheva
Categories: Technology & Engineering
Type: BOOK - Published: 2014-09-09 - Publisher: John Wiley & Sons

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.
Combining Pattern Classifiers
Language: en
Pages: 373
Authors: Ludmila I. Kuncheva
Categories: Technology & Engineering
Type: BOOK - Published: 2004-08-20 - Publisher: John Wiley & Sons

Covering pattern classification methods, Combining Classifiers: Ideas and Methods focuses on the important and widely studied issue of how to combine several classifiers together in order to achieve improved recognition performance. It is one of the first books to provide unified, coherent, and expansive coverage of the topic and as
Artificial Intelligence and Soft Computing – ICAISC 2008
Language: en
Pages: 1275
Authors: Leszek Rutkowski, Ryszard Tadeusiewicz, Lofti A. Zadeh, Jacek M. Zurada
Categories: Computers
Type: BOOK - Published: 2008-06-16 - Publisher: Springer Science & Business Media

computing techniques.
Multiple Classifier Systems
Language: en
Pages: 440
Authors: Nikunj C. Oza, Robi Polikar, Josef Kittler, Fabio Roli
Categories: Computers
Type: BOOK - Published: 2005-06 - Publisher: Springer Science & Business Media

This book constitutes the refereed proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005, held in Seaside, CA, USA in June 2005. The 42 revised full papers presented were carefully reviewed and are organized in topical sections on boosting, combination methods, design of ensembles, performance analysis, and
Multiple Classifier Systems
Language: en
Pages: 524
Authors: Michal Haindl, Josef Kittler, Fabio Roli
Categories: Computers
Type: BOOK - Published: 2007-06-21 - Publisher: Springer

This book constitutes the refereed proceedings of the 7th International Workshop on Multiple Classifier Systems, MCS 2007, held in Prague, Czech Republic in May 2007. It covers kernel-based fusion, applications, boosting, cluster and graph ensembles, feature subspace ensembles, multiple classifier system theory, intramodal and multimodal fusion of biometric experts, majority