Ensemble methods [electronic resource] : foundations and algorithms

상세정보

자료유형	단행본
서명/저자사항	Ensemble methods [electronic resource]: foundations and algorithms / Zhi-Hua Zhou.
개인저자	Zhou, Zhi-Hua, Ph. D.
발행사항	Boca Raton, FL: Taylor & Francis, 2012.
형태사항	1 online resource.
총서사항	Chapman & Hall/CRC machine learning & pattern recognition series
기타형태 저록	Print Version: Zhou, Zhi-Hua, Ph. D. Ensemble methods. Boca Raton, FL : Taylor & Francis, 2012 9781439830031
ISBN	9781439830055 (electronic bk.) 1439830053 (electronic bk.)
서지주기	Includes bibliographical references and index.
내용주기	Boosting -- Bagging -- Combination Methods -- Diversity -- Ensemble Pruning -- Clustering Ensembles -- Advanced Topics.
요약	"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"--
해제	Provided by publisher.
일반주제명	Multiple comparisons (Statistics) Set theory. Mathematical analysis. BUSINESS & ECONOMICS / Statistics COMPUTERS / Database Management / Data Mining COMPUTERS / Machine Theory MATHEMATICS / Probability & Statistics / Multivariate Analysis
분류기호(DDC)	519.535
언어	영어
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