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Dependence-space-based attribute reductions in inconsistent decision information systems
DOI:10.1016/j.ijar.2008.06.004.png)
摘要
En 中文
In rough set theory, attribute reduction is an important mechanism for knowledge discovery. This paper mainly deals with attribute reductions of an inconsistent decision information system based on a dependence space. Through the concept of inclusion degree, a generalized decision distribution function is first constructed. A decision distribution relation is then defined. On the basis of this decision distribution relation, a dependence space is proposed, and an equivalence congruence based on the indiscernibility attribute sets is also obtained. Applying the congruences on a dependence space, new approaches to find a distribution consistent set are formulated. The judgement theorems for judging distribution consistent sets are also established by using these congruences and the decision distribution relation. (C) 2008 Elsevier Inc. All rights reserved.
Keyword:
Congruence
Decision information system
Decision distribution relation
Dependence space
Generalized decision distribution function
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