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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 11/2018

02.01.2018 | Original Article

Fuzzy decision implication canonical basis

verfasst von: Yanhui Zhai, Deyu Li, Kaishe Qu

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 11/2018

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Abstract

Fuzzy decision implication (FDI) is regarded as a basic form of knowledge representation in fuzzy decision based formal concept analysis. How to reduce redundant FDIs and generate an informative and minimal set of FDIs from a given set of FDIs is the main concern in the study of FDI. This paper introduces fuzzy decision premise, constructs fuzzy decision implication canonical basis (FD canonical basis) and proves that FD canonical basis is complete, non-redundant and optimal, i.e., FD canonical basis contains the least number of FDIs among all complete sets of FDIs. Thus, from a given set of FDIs, one can generate its corresponding FD canonical basis, which turns out to be informative (complete) and minimal (optimal).
Vorheriger Artikel Relation granulation and algebraic structure based on concept lattice in complex information systems
Nächster Artikel Synthesizing decision rules from multiple information sources: a neighborhood granulation viewpoint

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Metadaten
Titel
Fuzzy decision implication canonical basis
verfasst von
Yanhui Zhai
Deyu Li
Kaishe Qu
Publikationsdatum
02.01.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 11/2018
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-017-0780-7

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