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Ensemble methods : = foundations and...

Zhou, Zhi-Hua, (Ph. D.)

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Ensemble methods : = foundations and algorithms /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Ensemble methods :/ Zhi-Hua Zhou.
其他題名:	foundations and algorithms /
作者:	Zhou, Zhi-Hua,
出版者:	Boca Raton, FL :Taylor & Francis, : c2012.,
面頁冊數:	xiv, 222 p. :ill. ;25 cm.
標題:	Mathematical analysis. -
ISBN:	1439830037

Ensemble methods : = foundations and algorithms /
Zhou, Zhi-Hua,Ph. D.

Ensemble methods :foundations and algorithms /Zhi-Hua Zhou. - Boca Raton, FL :Taylor & Francis,c2012. - xiv, 222 p. :ill. ;25 cm. - Chapman & Hall/CRC machine learning & pattern recognition series.

Includes bibliographical references 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"--

ISBN: 1439830037GBP59.00

LCCN: 2012014555Subjects--Topical Terms:

516833
Mathematical analysis.

LC Class. No.: QA278.4 / .Z47 2012

Dewey Class. No.: 006.3/1

Ensemble methods : = foundations and algorithms /
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245 1 0 $a Ensemble methods : $b foundations and algorithms / $c Zhi-Hua Zhou.
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300 $a xiv, 222 p. : $b ill. ; $c 25 cm.
490 0 $a Chapman & Hall/CRC machine learning & pattern recognition series
504 $a Includes bibliographical references and index.
520 $a "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"-- $c Provided by publisher.
650 0 $a Mathematical analysis. $3 516833
650 0 $a Multiple comparisons (Statistics) $3 565899
650 0 $a Set theory. $3 520081