Attribute reduction in decision-theoretic rough set model: a further investigation

  • Authors:

  • Huaxiong Li;Xianzhong Zhou;Jiabao Zhao;Dun Liu

  • Affiliations:

  • School of Management and Engineering, Nanjing University, Nanjing, Jiangsu, P.R. China and State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, P.R. China;School of Management and Engineering, Nanjing University, Nanjing, Jiangsu, P.R. China;School of Management and Engineering, Nanjing University, Nanjing, Jiangsu, P.R. China;School of Economics and Management, Southwest Jiaotong University, Chengdu, P.R. China

  • Venue:
  • RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
  • Year:
  • 2011

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Abstract

The monotonicity of positive region in PRS (Pawlak Rough Set) and DTRS (Decision-Theoretic Rough Set) are comparatively discussed in this paper. Theoretic analysis shows that the positive region in DTRS model may expand with the decrease of the attributes, which is essentially different from that of PRS model and leads to a new definition of attribute reduction in DTRS model. A heuristic algorithm for the newly defined attribute reduction in DTRS model is proposed, in which the positive region is allowed to expand instead of remaining unchanged in the process of deleting attributes. Results of experimental analysis are included to validate the theoretic analysis and quantify the effectiveness of the proposed attribute reduction algorithm.