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Variable Precision Multigranulation Rough Set and Attributes Reduction

  • Hengrong Ju
  • Xibei YangEmail author
  • Huili Dou
  • Jingjing Song
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8449)

Abstract

Multigranulation rough set is a new expansion of the classical rough set since the former uses a family of the binary relations instead of single one for the constructing of approximations. In this paper, the model of the variable precision rough set is introduced into the multigranulation environment and then the concept of the variable precision multigranulation rough set is proposed, which include optimistic and pessimistic cases. Not only basic properties of variable precision multigranulation rough set are investigated, but also the relationships among variable precision rough set, multigranulation rough set and variable precision multigranulation rough set are examined. Finally, a heuristic algorithm is presented for computing reducts of variable precision multigranulation rough set, it is also tested on five UCI data sets.

Keywords

Attributes reduction Multigranulation rough set Variable precision multigranulation rough set 

Notes

Acknowledgment

This work is supported by the Natural Science Foundation of China (Nos. 61100116, 61272419, 61305058), the Natural Science Foundation of Jiangsu Province of China (Nos. BK2011492, BK2012700, BK20130471), Qing Lan Project of Jiangsu Province of China, Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information (Nanjing University of Science and Technology), Ministry of Education (No. 30920130122005), Key Laboratory of Artificial Intelligence of Sichuan Province (No. 2013RYJ03), Natural Science Foundation of Jiangsu Higher Education Institutions of China (Nos. 13KJB520003, 13KJD520008), Postgraduate Innovation Foundation of University in Jiangsu Province of China under Grant No. CXLX13_707.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Hengrong Ju
    • 1
    • 2
  • Xibei Yang
    • 1
    • 3
    • 4
    Email author
  • Huili Dou
    • 1
    • 2
  • Jingjing Song
    • 1
    • 2
  1. 1.School of Computer Science and EngineeringJiangsu University of Science and TechnologyZhenjiangPeople’s Republic of China
  2. 2.Key Laboratory of Intelligent Perception and Systems for High-Dimensional InformationNanjing University of Science and Technology, Ministry of EducationNanjingPeople’s Republic of China
  3. 3.Artificial Intelligence Key Laboratory of Sichuan ProvinceZigongPeople’s Republic of China
  4. 4.School of Economics and ManagementNanjing University of Science and TechnologyNanjingPeople’s Republic of China

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