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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 6/2015

01.12.2015 | Original Article

Multigranulation decision-theoretic rough sets in incomplete information systems

verfasst von: Hai-Long Yang, Zhi-Lian Guo

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 6/2015

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Abstract

We study multigranulation decision-theoretic rough sets in incomplete information systems. Based on Bayesian decision procedure, we propose the notions of weighted mean multigranulation decision-theoretic rough sets, optimistic multigranulation decision-theoretic rough sets, and pessimistic multigranulation decision-theoretic rough sets in an incomplete information system. We investigate the relationships between the proposed multigranulation decision-theoretic rough set models and other related rough set models. We also study some basic properties of these models. We give an example to illustrate the application of the proposed models.
Vorheriger Artikel A matching model of mathematical expressions with FDS based index
Nächster Artikel Decision rules acquisition based on interval knowledge granules for incomplete ordered decision information systems

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Metadaten
Titel
Multigranulation decision-theoretic rough sets in incomplete information systems
verfasst von
Hai-Long Yang
Zhi-Lian Guo
Publikationsdatum
01.12.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 6/2015
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-015-0407-9

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