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Pattern classification using ensembl...
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Rokach, Lior.
Pattern classification using ensemble methods
Record Type:
Electronic resources : Monograph/item
Title/Author:
Pattern classification using ensemble methodsLior Rokach.
Author:
Rokach, Lior.
Published:
Singapore ;World Scientific Pub. Co.,c2010.
Description:
xv, 225 p. :ill.
Subject:
Pattern recognition systems.
Online resource:
http://www.worldscientific.com/worldscibooks/10.1142/7238#t=toc
ISBN:
9789814271073 (electronic bk.)
Pattern classification using ensemble methods
Rokach, Lior.
Pattern classification using ensemble methods
[electronic resource] /Lior Rokach. - Singapore ;World Scientific Pub. Co.,c2010. - xv, 225 p. :ill. - Series in machine perception and artificial intelligence ;v. 75. - Series in machine perception and artificial intelligence ;v. 74..
Includes bibliographical references (p. 185-222) and index.
Researchers from various disciplines such as pattern recognition, statistics, and machine learning have explored the use of ensemble methodology since the late seventies. Thus, they are faced with a wide variety of methods, given the growing interest in the field. This book aims to impose a degree of order upon this diversity by presenting a coherent and unified repository of ensemble methods, theories, trends, challenges and applications. The book describes in detail the classical methods, as well as the extensions and novel approaches developed recently. Along with algorithmic descriptions of each method, it also explains the circumstances in which this method is applicable and the consequences and the trade-offs incurred by using the method.
Electronic reproduction.
Singapore :
World Scientific Publishing Co.,
2010.
System requirements: Adobe Acrobat Reader.
ISBN: 9789814271073 (electronic bk.)Subjects--Topical Terms:
183725
Pattern recognition systems.
LC Class. No.: TK7882.P3
Dewey Class. No.: 006.4
Pattern classification using ensemble methods
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v. 75
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Includes bibliographical references (p. 185-222) and index.
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Researchers from various disciplines such as pattern recognition, statistics, and machine learning have explored the use of ensemble methodology since the late seventies. Thus, they are faced with a wide variety of methods, given the growing interest in the field. This book aims to impose a degree of order upon this diversity by presenting a coherent and unified repository of ensemble methods, theories, trends, challenges and applications. The book describes in detail the classical methods, as well as the extensions and novel approaches developed recently. Along with algorithmic descriptions of each method, it also explains the circumstances in which this method is applicable and the consequences and the trade-offs incurred by using the method.
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2010.
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http://www.worldscientific.com/worldscibooks/10.1142/7238#t=toc
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EB TK7882.P3 c2010
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http://www.worldscientific.com/worldscibooks/10.1142/7238#t=toc
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