Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 210700191-5.doi: 10.11896/jsjkx.210700191

• Big Data & Data Science • Previous Articles     Next Articles

Distribution Reduction in Fuzzy Order Decision Data Sets with Attention Degree

XU Wei-hua, ZHANG Jun-jie, CHEN Xiu-wei   

  1. College of Artificial Intelligence,Southwest University,Chongqing 400715,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:XU Wei-hua,born in 1979,Ph.D,professor,Ph.D supervisor,is a member of CAAI.His main research interests include cognitive computing,data mining,machine learning and so on.
  • Supported by:
    National Natural Science Foundation of China(61976245).

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Abstract: With the advent of the era of big data,the structure of data becomes more and more complex,and the dimensions of data set become higher and higher,which will affect the efficiency of data mining greatly.Therefore,it is necessary to perform data compression or attribute reduction to information systems,that is,to remove unnecessary redundant attributes,reduce data dimensions,and improve the efficiency of data mining.The reduction methods proposed by many scholars in the past regard each attribute as equally important.But in real life,people’s attention to each conditional attribute in the data set is often different.Aiming at this phenomenon,based on the classical fuzzy decision data set,this paper weights different conditional attributes,defines the weighted score function,and further establishes the fuzzy order decision information system with attention degree.Then the distribution function is introduced into the system and the distribution reduction method is established by the distribution discer-nible matrix.Finally,the feasibility of the method is verified by a case study.

Key words: Fuzzy set, Order decision data set, Attention degree, Distribution reduction, Distribution discernible matrix

CLC Number: 

  • TP18
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