Abstract
A Concept lattice is a special kind of lattice, the explicit representation of which can be viewed as a semantic network with special properties. Concept lattices have been applied to Machine Learning as well as to the uncovering of the underlying structure in discrete-valued data. They also embody the cladistic approach to classification. This paper describes how the use of a concept lattice as representation model is related to the rough set approach to data analysis and how operations of rough set theory can be implemented using a concept lattice.
On leave from the University of Pretoria, Pretoria, 0001, South Africa.
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© 1994 British Computer Society
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Oosthuizen, G.D. (1994). Rough Sets and Concept Lattices. In: Ziarko, W.P. (eds) Rough Sets, Fuzzy Sets and Knowledge Discovery. Workshops in Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3238-7_4
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DOI: https://doi.org/10.1007/978-1-4471-3238-7_4
Publisher Name: Springer, London
Print ISBN: 978-3-540-19885-7
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