A Theoretical Framework on the Ideal Number of Classifiers for Online Ensembles in Data Streams

Hamed R. Bonab, Fazli Can. A Theoretical Framework on the Ideal Number of Classifiers for Online Ensembles in Data Streams. In Snehasis Mukhopadhyay, ChengXiang Zhai, Elisa Bertino, Fabio Crestani, Javed Mostafa, Jie Tang, Luo Si, Xiaofang Zhou, Yi Chang, Yunyao Li, Parikshit Sondhi, editors, Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, USA, October 24-28, 2016. pages 2053-2056, ACM, 2016. [doi]

Abstract

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