Ensemble methods foundations and algorithms

"This comprehensive book presents an in-depth and systematic introduction to ensemble methods for researchers in machine learning, data mining, and related areas. It helps readers solve modem problems in machine learning using these methods. The author covers the spectrum of research in ensembl...

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Bibliographische Detailangaben
1. Verfasser: Zhou, Zhi-Hua (VerfasserIn)
Format: UnknownFormat
Sprache:eng
Veröffentlicht: Boca Raton, Fla. u.a. CRC Press, Taylor & Francis 2012
Schriftenreihe:Machine Learning & Pattern Recognition Series
Schlagworte:
Online Zugang:Inhaltsverzeichnis
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Beschreibung
Zusammenfassung:"This comprehensive book presents an in-depth and systematic introduction to ensemble methods for researchers in machine learning, data mining, and related areas. It helps readers solve modem problems in machine learning using these methods. The author covers the spectrum of research in ensemble methods, including such famous methods as boosting, bagging, and rainforest, along with current directions and methods not sufficiently addressed in other books. Chapters explore cutting-edge topics, such as semi-supervised ensembles, cluster ensembles, and comprehensibility, as well as successful applications"--
Beschreibung:Formerly CIP Uk. - Includes bibliographical references (p. 187-218) and index
Beschreibung:XIV, 222 S.
graph. Darst.
25 cm
ISBN:9781439830031
978-1-4398-3003-1
1439830037
1-4398-3003-7