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Analyzing rough set based attribute reductions by extension rule

  • Bing Li
  • , Tommy W.S. Chow
  • , Peng Tang

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

An improved discernibility function for rough set based attribute reduction is defined to keep discernibility ability and remove redundant attributes without the precondition of the Positive Region. On the basis of discernibility function, the solution of rough set based attribute reduction can be found by satisfiability methods. With extension rule theory, a satisfiability method, the distribution of solutions with different number of attributes is obtained without enumerating all attribute reductions. Then, it is easy to search the attribute reduction with the smallest number of attributes. In addition, the cost of space and time is analyzed to find factors playing role in the computation of the method. © 2013 Elsevier B.V.
Original languageEnglish
Pages (from-to)185-196
JournalNeurocomputing
Volume123
DOIs
Publication statusPublished - 10 Jan 2014

Research Keywords

  • Attribute reduction
  • Extension rule
  • Reduction distribution
  • Rough set

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