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| Titre : | Data Classification: Algorithms and Applications |
| Auteurs : | Charu Aggarwal, Auteur |
| Type de document : | document électronique |
| Editeur : | [S.l.] : Chapman and Hall/CRC, 2014 |
| ISBN/ISSN/EAN : | 978-1-4665-8674-1 |
| Résumé : |
*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-*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. |
