Probabilistic rough set approximations

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Probabilistic rough set approximations
This paper reviews probabilistic approaches to rough sets in granulation, approximation, and rule induction. The Shannon entropy function is used to quantitatively characterize partitions of a universe. Both algebraic and probabilistic rough set approximations are studied. The probabilistic approximations are defined in a decision-theoretic framework. The problem of rule induction, a major application of rough set theory, is studied in probabilistic and information-theoretic terms. Two types of rules are analyzed, the local, low order rules, and the global, high order rules.
Yiyu Yao
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2008
Where IJAR
Authors Yiyu Yao
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