Incomplete Multigranulation Rough Set

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Incomplete Multigranulation Rough Set
The original rough-set model is primarily concerned with the approximations of sets described by a single equivalence relation on a given universe. With granular computing point of view, the classical rough-set theory is based on a single granulation. This correspondence paper first extends the rough-set model based on a tolerance relation to an incomplete rough-set model based on multigranulations, where set approximations are defined through using multiple tolerance relations on the universe. Then, several elementary measures are proposed for this rough-set framework, and a concept of approximation reduct is introduced to characterize the smallest attribute subset that preserves the lower approximation and upper approximation of all decision classes in this rough-set model. Finally, several key algorithms are designed for finding an approximation reduct.
Yuhua Qian, Jiye Liang, Chuangyin Dang
Added 22 May 2011
Updated 22 May 2011
Type Journal
Year 2010
Where TSMC
Authors Yuhua Qian, Jiye Liang, Chuangyin Dang
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