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Data classification :algorithms and ...

Aggarwal, Charu C.

Data classification :algorithms and applications /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Data classification :edited by Charu C. Aggarwal.
Reminder of title:	algorithms and applications /
other author:	Aggarwal, Charu C.
Published:	Boca Raton :CRC Press, Taylor & Francis Group,c2015.
Description:	xxvii, 671 p., [8] p. of plates :ill. (some col.) ;26 cm.
Notes:	"A Chapman & Hall book."
Subject:	File organization (Computer science)
ISBN:	9781466586741 (hbk.) :

Data classification :algorithms and applications /
Data classification :algorithms and applications /edited by Charu C. Aggarwal. - Boca Raton :CRC Press, Taylor & Francis Group,c2015. - xxvii, 671 p., [8] p. of plates :ill. (some col.) ;26 cm. - Chapman & Hall/CRC data mining and knowledge discovery series.

"A Chapman & Hall book."

Includes bibliographical references and index.

"Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains, including text, multimedia, social network, and biological data.This comprehensive book focuses on three primary aspects of data classification:MethodsThe book first describes common techniques used for classification, including probabilistic methods, decision trees, rule-based methods, instance-based methods, support vector machine methods, and neural networks. DomainsThe book then examines specific methods used for data domains such as multimedia, text, time-series, network, discrete sequence, and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm. VariationsThe book concludes with insight on variations of the classification process. It discusses ensembles, rare-class learning, distance function learning, active learning, visual learning, transfer learning, and semi-supervised learning as well as evaluation aspects of classifiers"--

ISBN: 9781466586741 (hbk.) :NT$2494

LCCN: 2013050912Subjects--Topical Terms:

199305
File organization (Computer science)

LC Class. No.: QA76.9.F5 / .D38 2015

Dewey Class. No.: 005.74/1

Data classification :algorithms and applications /
LDR:02857cam a2200253 a 4500 001 457921
003 DLC
005 20150406141254.0
008 150922s2015 fluaf b 001 0 eng
010 $a 2013050912
020 $a 9781466586741 (hbk.) : $c NT$2494
020 $a 1466586745 (hbk.)
035 $a 2013050912
040 $a DLC $b eng $c DLC $d DLC
042 $a pcc
050 0 0 $a QA76.9.F5 $b .D38 2015
082 0 0 $a 005.74/1 $2 23
245 0 0 $a Data classification : $b algorithms and applications / $c edited by Charu C. Aggarwal.
260 $a Boca Raton : $b CRC Press, Taylor & Francis Group, $c c2015.
300 $a xxvii, 671 p., [8] p. of plates : $b ill. (some col.) ; $c 26 cm.
490 0 $a Chapman & Hall/CRC data mining and knowledge discovery series
500 $a "A Chapman & Hall book."
504 $a Includes bibliographical references and index.
520 $a "Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains, including text, multimedia, social network, and biological data.This comprehensive book focuses on three primary aspects of data classification:MethodsThe book first describes common techniques used for classification, including probabilistic methods, decision trees, rule-based methods, instance-based methods, support vector machine methods, and neural networks. DomainsThe book then examines specific methods used for data domains such as multimedia, text, time-series, network, discrete sequence, and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm. VariationsThe book concludes with insight on variations of the classification process. It discusses ensembles, rare-class learning, distance function learning, active learning, visual learning, transfer learning, and semi-supervised learning as well as evaluation aspects of classifiers"-- $c Provided by publisher.
520 $a "This book homes in on three primary aspects of data classification: the core methods for data classification including probabilistic classification, decision trees, rule-based methods, and SVM methods; different problem domains and scenarios such as multimedia data, text data, biological data, categorical data, network data, data streams and uncertain data: and different variations of the classification problem such as ensemble methods, visual methods, transfer learning, semi-supervised methods and active learning. These advanced methods can be used to enhance the quality of the underlying classification results"-- $c Provided by publisher.
650 0 $a File organization (Computer science) $3 199305
650 0 $a Categories (Mathematics) $3 206297
650 0 $a Algorithms. $3 184661
700 1 $a Aggarwal, Charu C. $3 264940