An Incremental Updating Algorithm for Core Computing in Dominance-Based Rough Set Model

  • Authors:
  • Xiuyi Jia;Lin Shang;Yangsheng Ji;Weiwei Li

  • Affiliations:
  • National Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210093, China;National Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210093, China;National Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210093, China;College of Automation, Chongqing University, Chongqing, 400030, China

  • Venue:
  • RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
  • Year:
  • 2009

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Abstract

This paper analyzes incremental updating for core computing in a dominance-based rough set model, which extends previous reduct studies in capability of dynamic updating and dominance relation. Then we redefine the dominance discernibility matrix and present an incremental updating algorithm. In this algorithm, when new samples arrive, the proposed solution only involves a few modifications to relevant rows and columns in the dominance discernibility matrix instead of recalculation.Both of theoretical analysis and experimental results show that the algorithm is effective and efficient in dynamic computation.