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Ensemble methods : = foundations and...

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

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Ensemble methods : = foundations and algorithms /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Ensemble methods :/ Zhi-Hua Zhou.
Reminder of title:	foundations and algorithms /
Author:	Zhou, Zhi-Hua,
Published:	Boca Raton, FL :Taylor & Francis, : c2012.,
Description:	xiv, 222 p. :ill. ;25 cm.
Subject:	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 /
LDR:01291cam a2200205 a 4500 001 2012587
005 20130208143200.0
008 160811s2012 flua b 001 0 eng
010 $a 2012014555
020 $a 1439830037 $q (hbk.) : $c GBP59.00
020 $a 9781439830031 $q (hbk.)
040 $a DLC $c DLC
042 $a pcc
050 0 0 $a QA278.4 $b .Z47 2012
082 0 0 $a 006.3/1 $2 23
100 1 $a Zhou, Zhi-Hua, $c Ph. D. $3 2170807
245 1 0 $a Ensemble methods : $b foundations and algorithms / $c Zhi-Hua Zhou.
260 $a Boca Raton, FL : $b Taylor & Francis, $c c2012.
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