An edition of Data classification (2014)

Data classification

algorithms and applications

  • 2 Want to read
Data classification
Charu C. Aggarwal, Charu C. Ag ...
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Last edited by MARC Bot
December 15, 2022 | History
An edition of Data classification (2014)

Data classification

algorithms and applications

  • 2 Want to read

"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"--

"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"--

Publish Date
Language
English
Pages
671

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Edition Availability
Cover of: Data Classification
Data Classification
2020, Taylor & Francis Group
in English
Cover of: Data Classification
Data Classification: Algorithms and Applications
2014, Taylor & Francis Group
in English
Cover of: Data Classification
Data Classification
2014, Taylor & Francis Group
in English
Cover of: Data classification
Data classification: algorithms and applications
2014, CRC Press, Taylor & Francis Group
in English
Cover of: Data Classification
Data Classification: Algorithms and Applications
2014, Taylor & Francis Group
in English
Cover of: Data Classification
Data Classification: Algorithms and Applications
2014, Taylor & Francis Group
in English

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Book Details


Edition Notes

"A Chapman & Hall book."

Includes bibliographical references and index.

Published in
Boca Raton
Series
Chapman & Hall/CRC data mining and knowledge discovery series
Copyright Date
2014

Classifications

Dewey Decimal Class
005.74/1
Library of Congress
QA76.9.F5 .D38 2014, QA76.9.F5.D38 2014, QA76.9.F5 D38 2015

The Physical Object

Pagination
xxvii, 671 pages
Number of pages
671

ID Numbers

Open Library
OL31186542M
ISBN 10
1466586745
ISBN 13
9781466586741
LCCN
2013050912
OCLC/WorldCat
890721171

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December 15, 2022 Edited by MARC Bot import existing book
September 17, 2021 Edited by ImportBot import existing book
November 14, 2020 Created by MARC Bot import new book