Data classification : algorithms and applications

Responsibility edited by Charu C. Aggarwal, IBM T.J. Watson Research Center, Yorktown Heights, New York, USA. Publication Boca Raton : CRC Press, [2015] Copyright notice ©20 ©2015 Physical description 1 online resource (xxvii, 671 pages) : illustrations (some color) Series Chapman & Hall/CRC data mining and knowledge discovery series.

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Creators/Contributors

Contributor Aggarwal, Charu C., editor.

Contents/Summary

• An Introduction to Data Classification Charu C. Aggarwal
• Feature Selection for Classification: A Review Jiliang Tang, Salem Alelyani, and Huan Liu
• Probabilistic Models for Classification Hongbo Deng, Yizhou Sun, Yi Chang, and Jiawei Han
• Decision Trees: Theory and Algorithms Victor E. Lee, Lin Liu, and Ruoming Jin
• Rule-Based Classification Xiao-Li Li and Bing Liu
• Instance-Based Learning: A Survey Charu C. Aggarwal
• Support Vector Machines Po-Wei Wang and Chih-Jen Lin
• Neural Networks: A Review Alain Biem
• A Survey of Stream Classification Algorithms Charu C. Aggarwal
• Big Data Classification Hanghang Tong
• Text Classification Charu C. Aggarwal and ChengXiang Zhai
• Multimedia Classification Shiyu Chang, Wei Han, Xianming Liu, Ning Xu, Pooya Khorrami, and Thomas S. Huang
• Time Series Data Classification Dimitrios Kotsakos and Dimitrios Gunopulos
• Discrete Sequence Classification Mohammad Al Hasan
• Collective Classification of Network Data Ben London and Lise Getoor
• Uncertain Data Classification Reynold Cheng, Yixiang Fang, and Matthias Renz
• Rare Class Learning Charu C. Aggarwal
• Distance Metric Learning for Data Classification Fei Wang
• Ensemble Learning Yaliang Li, Jing Gao, Qi Li, and Wei Fan
• Semi-Supervised Learning Kaushik Sinha
• Transfer Learning Sinno Jialin Pan
• Active Learning: A Survey Charu C. Aggarwal, Xiangnan Kong, Quanquan Gu, Jiawei Han, and Philip S. Yu
• Visual Classification Giorgio Maria Di Nunzio
• Evaluation of Classification Methods Nele Verbiest, Karel Vermeulen, and Ankur Teredesai
• Educational and Software Resources for Data Classification Charu C. Aggarwal
• Index.
• (source: Nielsen Book Data)

• An Introduction to Data Classification. Feature Selection for Classification: A Review. Probabilistic Models for Classification. Decision Trees: Theory and Algorithms. Rule-Based Classification. Instance-Based Learning: A Survey. Support Vector Machines. Neural Networks: A Review. A Survey of Stream Classification Algorithms. Big Data Classification. Text Classification. Multimedia Classification. Time Series Data Classification. Discrete Sequence Classification. Collective Classification of Network Data. Uncertain Data Classification. Rare Class Learning. Distance Metric Learning for Data Classification. Ensemble Learning. Semi-Supervised Learning. Transfer Learning. Active Learning: A Survey. Visual Classification. Evaluation of Classification Methods. Educational and Software Resources for Data Classification. Index.
• (source: Nielsen Book Data)

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Bibliographic information

Publication date 2015 Copyright date 2015 Series Chapman & Hall/CRC data mining and knowledge discovery series Note "A Chapman & Hall book." ISBN 9781466586758 (e-book ; PDF) 1466586753 (e-book ; PDF) 9780429102639 (electronic bk.) 0429102631 (electronic bk.) 9781466586741 (hardback ; acid-free paper) 1466586745 (hardback ; acid-free paper)

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Start at call number: QA76.9.F5 D38 2015