2024-03-28T12:52:08Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1343202024-03-13T09:52:56Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134243
Michał, Woźniak
Graña Romay, Manuel
Corchado Rodríguez, Emilio Santiago
2017-09-05T10:59:40Z
2017-09-05T10:59:40Z
2014
Information Fusion. Volumen 16, pp. 3-17. Elsevier BV.
1566-2535 (Print)
http://hdl.handle.net/10366/134320
A current focus of intense research in pattern classification is the combination of several classifier systems, which can be built following either the same or different models and/or datasets building approaches. These systems perform information fusion of classification decisions at different levels overcoming limitations of traditional approaches based on single classifiers. This paper presents an up-to-date survey on multiple classifier system (MCS) from the point of view of Hybrid Intelligent Systems. The article discusses major issues, such as diversity and decision fusion methods, providing a vision of the spectrum of applications that are currently being developed.
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Elsevier BV
Attribution-NonCommercial-NoDerivs 3.0 Unported
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
Computer Science
A survey of multiple classifier systems as hybrid systems
info:eu-repo/semantics/article