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Concept lattices in rough set theory [PDF]

IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04., 2004
An alternative formulation of rough set theory can be developed based on a binary relation between two universes, one is a finite set of objects and the other is a finite set of properties. Rough set approximation operators are defined with respect to the binary relation. Three concept lattices are constructed based on approximation operators. They are
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Rough Set Theory: An Introduction

2002
In rough set theory, knowledge is interpreted as an ability to classify some objects (cf. [Pawlak82a, 81b]). These objects form a set called often a universe of discourse and their nature may vary from case to case: they may be e.g. medical patients, processes, participants in a conflict etc., etc.
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The concept learning in the theory of rough sets

2008 International Conference on Machine Learning and Cybernetics, 2008
Knowledge reduction in decision table is important in both theory and application, and it outputs a minimal algorithm as a result. Set of the samples fitting the minimal algorithm is a concept over the set of all possible instances. But in unfamiliar environment, decision table is obtained randomly.
Qun-Feng Zhang, Zhi-Qiang Li, Yu-ting Jiang   +2 more
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On Generalizing Rough Set Theory

2007
This paper summarizes various formulations of the standard rough set theory. It demonstrates how those formulations can be adopted to develop different generalized rough set theories. The relationships between rough set theory and other theories are discussed.
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Rough Set Theory Fundamentals

2018
The rough set theory was proposed by Polish scientist Zdzislaw Pawlak. The first paper containing an outline of the theory was published in 1982 in the International Journal of Computer and Information Sciences Pawlak (Int J Comput Inf Sci 11:341–356, 1982 [14]).
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α-RST: a generalization of rough set theory

Information Sciences, 2000
The paper presents an approach called Alpha Rough Set Theory (\(\alpha\)-RST) as a generalization of rough set approach. The values of attributes in information systems are assumed to be pairs \((\ell,v)\) consisting of the linguistic variable \(\ell\) and the value \(v\) of the fuzzy membership function corresponding to the linguistic variable 1 ...
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Rough Approximate Operators: Axiomatic Rough Set Theory

1994
In rough set theory, the upper and lower approximations are defined in terms of equivalence relation. In this paper, the reverse problem is considered. Let H and L are two abstract operators acting on the power set of U, the universe of discourse. If the two operators satisfy six axioms, then there is an equivalence relation defined on U such that H(X)
Tsau Young Lin, Qing Liu
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Object Reduction in Rough Set Theory

2019
This chapter deals with object reduction in rough set theory. We introduce a concept of object reduction that reduces the number of objects as long as possible with keeping the results of attribute reduction in the original decision table.
Tetsuya Murai, Yasuo Kudo, Seiki Akama
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Review on Application of Rough Set Theory

Advanced Materials Research, 2013
Rough set theory has found an increasingly wide utilization since it was promoted in 1980s.And study on the application of rough set theory in every field has a great development in recent years. Application of rough set theory in attribute reduction, continuous attributes discretization, and uncertainty measuring, as well as application of information
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A Survey on Rough Set Theory and Applications

Chinese Journal of Computers, 2009
Hong Yu, Yiyu Yao, Guo-Yin Wang
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