Data Classification : Algorithms and Applications
Language: English
Published by Chapman And Hall/CRC, 2014
Series: Book 32 of 56 - Chapman & Hall/CRC Data Mining and Knowledge Discovery
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - Research 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, this book 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. It presents core methods in data classification, covers recent problem domains, and discusses advanced methods for enhancing the quality of the underlying classification results.
Seller Inventory # 9781466586741
- Title
- Data Classification : Algorithms and Applications
- Author
- Charu C. Aggarwal
- Publisher
- Chapman And Hall/CRC
- Publication year
- 2014
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1466586745
- ISBN 13
- 9781466586741
- Item weight
- 1,504 grams
- Dimensions
- 260x183x42 mm
- Series
- Book 32 of 56: Chapman & Hall/CRC Data Mining and Knowledge Discovery
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:
- Methods: The 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.
- Domains: The 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.
- Variations: The 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.
"Synopsis" may belong to another edition of this title.
About the Author
Charu C. Aggarwal is a research scientist at the IBM T.J. Watson Research Center. A fellow of the IEEE and the ACM, he is the author/editor of ten books, an associate editor of several journals, and the vice-president of the SIAM Activity Group on Data Mining. Dr. Aggarwal has published over 200 papers, has applied for or been granted over 80 patents, and has received numerous honors, including the IBM Outstanding Technical Achievement Award and EDBT 2014 Test of Time Award. His research interests include performance analysis, databases, and data mining. He earned a Ph.D. from the Massachusetts Institute of Technology.
"About the title" may belong to another edition of this title.
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