Incomplete multigranulation rough set

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)22_Publication in policy or professional journal

317 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Article number5353643
Pages (from-to)420-431
Journal / PublicationIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
Volume40
Issue number2
Publication statusPublished - Mar 2010

Abstract

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. © 2009 IEEE.

Research Area(s)

  • Attribute reduction, Granular computing, Information systems (ISs), Rough set