A Comparative Study of Algebra Viewpoint and Information Viewpoint in Attribute Reduction

  • Authors:

  • Guoyin Y. Wang;Jun Zhao;Jiujiang An;Yu Wu

  • Affiliations:

  • Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China. E-mais: wanggy,zhaojun,wuyu@cqupt.edu.cn/ anjiujiang@tom.com;Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China. E-mais: wanggy,zhaojun,wuyu@cqupt.edu.cn/ anjiujiang@tom.com;Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China. E-mais: wanggy,zhaojun,wuyu@cqupt.edu.cn/ anjiujiang@tom.com;Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China. E-mais: wanggy,zhaojun,wuyu@cqupt.edu.cn/ anjiujiang@tom.com

  • Venue:
  • Fundamenta Informaticae
  • Year:
  • 2005

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Abstract

Attribute reduction is an important issue in rough set theory and has already been studied from the algebra viewpoint and information viewpoint of rough set theory respectively. However, the concepts of attribute reduction based on these two different viewpoints are not equivalent to each other. In this paper, we make a comparative study on the quantitative relationship between some basic concepts of rough set theory like attribute reduction, attribute significance and core defined from these two viewpoints. The results show that the relationship between these conceptions from the two viewpoints is rather an inclusion than an equivalence due to the fact that the rough set theory discussed from the information point of view restricts attributes and decision tables more specifically than it does when considered from the algebra point of view. The identity of the two viewpoints will hold in consistent information decision tables only. That is, the algebra viewpoint and information viewpoint are equivalent for a consistent decision table, while different for an inconsistent decision table. The results are significant for the design and development of methods for information reduction.