Several approaches to attribute reduction in variable precision rough set model

  • Authors:
  • Masahiro Inuiguchi

  • Affiliations:
  • Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, Osaka, Japan

  • Venue:
  • MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
  • Year:
  • 2005

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Abstract

In this paper, we discuss attribute reduction in variable precision rough set model. We consider several kinds of reducts preserving some of lower approximations, upper approximations, boundary regions and the unpredictable region. We show relations among those kinds of reducts. Moreover we discuss logical function representations of the preservation of lower approximations, upper approximations, boundary regions and the unpredictable region as a basis for reduct calculation. By those discussions, the great difference between the analysis using variable precision rough sets and the classical rough set analysis is emphasized.