Rough set approximations in formal concept analysis

  • Authors:

  • Daisuke Yamaguchi;Atsuo Murata;Guo-Dong Li;Masatake Nagai

  • Affiliations:

  • Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan;Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan;Graduate School of System Design, Tokyo Metroporitan University, Hino, Japan;Faculty of Engineering, Kanagawa University, Yokohama, Japan

  • Venue:
  • Transactions on rough sets XII
  • Year:
  • 2010

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Abstract

Conventional set approximations are based on a set of attributes; however, these approximations cannot relate an object to the corresponding attribute. In this study, a new model for set approximation based on individual attributes is proposed for interval-valued data. Defining an indiscernibility relation is omitted since each attribute value itself has a set of values. Two types of approximations, single- and multiattribute approximations, are presented. A multi-attribute approximation has two solutions: a maximum and a minimum solution. A maximum solution is a set of objects that satisfy the condition of approximation for at least one attribute. A minimum solution is a set of objects that satisfy the condition for all attributes. The proposed set approximation is helpful in finding the features of objects relating to condition attributes when interval-valued data are given. The proposed model contributes to feature extraction in interval-valued information systems.