Dominance-based rough set approach to incomplete interval-valued information system

  • Authors:

  • Xibei Yang;Dongjun Yu;Jingyu Yang;Lihua Wei

  • Affiliations:

  • School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, PR China and Department of Computer Science, San José State University, San J ...;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, PR China;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, PR China;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, PR China

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2009

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Abstract

Since preference order is a crucial feature of data concerning decision situations, the classical rough set model has been generalized by replacing the indiscernibility relation with a dominance relation. The purpose of this paper is to further investigate the dominance-based rough set in incomplete interval-valued information system, which contains both incomplete and imprecise evaluations of objects. By considering three types of unknown values in the incomplete interval-valued information system, a data complement method is used to transform the incomplete interval-valued information system into a traditional one. To generate the optimal decision rules from the incomplete interval-valued decision system, six types of relative reducts are proposed. Not only the relationships between these reducts but also the practical approaches to compute these reducts are then investigated. Some numerical examples are employed to substantiate the conceptual arguments.