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Combining Pattern Classifiers - Methods And Algorithms 2nd Edition (Cód: 9237060)

Kuncheva,Ludmila I

John Wiley & Sons

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Descrição

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. 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.

Características

Produto sob encomenda Sim
Marca John Wiley & Sons
Cód. Barras 9781118315231
Altura 23.62 cm
I.S.B.N. 9781118315231
Profundidade 2.79 cm
Referência 024805247
Acabamento Capa dura
Número da edição 2
Ano da edição 2014
Idioma Inglês
Número de Páginas 384
Peso 0.75 Kg
Largura 15.75 cm
AutorKuncheva,Ludmila I

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Você está revisando: Combining Pattern Classifiers - Methods And Algorithms 2nd Edition

Combining Pattern Classifiers - Methods And Algorithms 2nd Edition (Cód: 9237060) Combining Pattern Classifiers - Methods And Algori... (Cód: 9237060)
R$ 615,50
Combining Pattern Classifiers - Methods And Algorithms 2nd Edition (Cód: 9237060) Combining Pattern Classifiers - Methods And Algori... (Cód: 9237060)
R$ 615,50