Rough set approximation based on dynamic granulation

  • Authors:

  • Jiye Liang;Yuhua Qian;Chengyuan Chu;Deyu Li;Junhong Wang

  • Affiliations:

  • School of Computer and Information Technology, Shanxi University, Taiyuan, People's Republic of China;School of Computer and Information Technology, Shanxi University, Taiyuan, People's Republic of China;Institute of Computing Technology, the Chinese Academy of Sciences, Beijing, People's Republic of China;School of Computer and Information Technology, Shanxi University, Taiyuan, People's Republic of China;School of Computer and Information Technology, Shanxi University, Taiyuan, People's Republic of China

  • Venue:
  • RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
  • Year:
  • 2005

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Abstract

In this paper, the concept of a granulation order is proposed in an information system. The positive approximation of a set under a granulation order is defined. Some properties of positive approximation are obtained. For a set of the universe in an information system, its approximation accuracy is monotonously increasing under a granulation order. This means that a proper family of granulations can be chosen for a target concept approximation according to the user requirements. An algorithm based on positive approximation is designed for decision rule mining, and its application is illustrated by an example.