Data Classification /
Material type: TextPublisher: Chapman and Hall/CRC, 2015Edition: 1st editionDescription: 1 online resource (707 pages)Subject(s): DDC classification:- 005.741
Item type | Current library | Collection | Call number | Status | Date due | Barcode | |
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Books | Botho University Botswana Open Shelves | Information Technology | 005.741 DAT (Browse shelf(Opens below)) | Available | BU-LIB22610 | ||
Books | Botho University Botswana Open Shelves | Information Technology | 005.741 DAT (Browse shelf(Opens below)) | Available | BU-LIB22611 |
Comprehensive Coverage of the Entire Area of Classification 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, 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: T he 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.
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