Earticle

초록

영어

The fuzziness and randomness of decision table affect hugely on the performance of knowledge acquisition in rough set. In order to reduce their influence, a novel reduction algorithm based on grey relational analysis is proposed. In the algorithm, every value of decision table is converted to the same domain. Moreover, on the basis of grey relational analysis, the grey relational matrix for the converted decision table is constructed to describe the equivalence relations between samples of decision table. Finally, the samples with the same similar level are adopted as the coarser granularity. The experiments fully show that the reduction decision table achieved almost the same recognition rate with less than one tenth of the former conditions. It fully shows the effectiveness of the algorithm.

목차

Abstract
 1. Introduction
 2. Fundamental Concepts
  2.1. Reduction Decision Table in Rough Set
  2.2. Grey Relational Analysis
 3. Reduction Algorithm for Decision Table based on Grey Relational Analysis
 4. Experiment and Analysis
 6. Conclusions
 Acknowledgements
 References

키워드

저자

• Jin Dai [ School of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P. R. China ]
• Xin Liu [ School of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P. R. China ]
• Feng Hu [ College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P. R. China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605