Ensemble methods : foundations and algorithms

By:

Zhou, Zhi-Hua

Material type: Text

9781439830031

Subject(s):

DDC classification:

006.31 23 ZHO-E

LOC classification:

QA278.4 .Z47 2012

Other classification:

BUS061000 | COM021030 | COM037000

Summary: "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"--

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Books	IIITD Reference	Computer Science and Engineering	REF 006.31 ZHO-E (Browse shelf(Opens below))	Available		003923

Total holds: 0

Includes bibliographical references (p. 187-218) and index.

"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"--

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