DE2: Dynamic ensemble of ensembles for learning nonstationary data-Reference-Cited by-同舟云学术

DE2: Dynamic ensemble of ensembles for learning nonstationary data

Published:2015-10 Issue: Volume:165 Page:14-22
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Yin Xu-Cheng,Huang Kaizhu,Hao Hong-Wei

Funder

National Basic Research Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference53 articles.

1. Dynamic weighted majority;Kolter;J. Mach. Learn. Res.,2007

2. Incremental learning of concept drift in nonstationary environments;Elwell;IEEE Trans. Neural Netw.,2011

3. Learning in nonstationary and evolving environments (Guest Editorial);Polikar;IEEE Trans. Neural Netw. Learn. Syst.,2014

4. J. Schlimmer, R. Granger, Beyond incremental processing: tracking concept drift, in: Proceedings of National Conference on Artificial Intelligence, 1986, pp. 502–507.

5. Learning in the presence of concept drift and hidden contexts;Widmer;Mach. Learn.,1996

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