Computer Science ›› 2022, Vol. 49 ›› Issue (5): 152-158.doi: 10.11896/jsjkx.210300302

• Database & Big Data & Data Science • Previous Articles     Next Articles

Efficient Neighborhood Covering Model Based on Triangle Inequality Checkand Local Strategy

CHEN Yu-si, AI Zhi-hua, ZHANG Qing-hua   

  1. Chongqing Key Laboratory of Computational Intelligence,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
  • Received:2021-03-31 Revised:2021-10-24 Online:2022-05-15 Published:2022-05-06
  • About author:CHEN Yu-si,born in 1994,postgra-duate.His main research interests include rough sets,machine learning and uncertain information processing.
  • Supported by:
    National Natural Science Foundation of China(61876201).

Abstract: Neighborhood covering model is widely used in classification tasks for its simple mechanism and ability to handle complex data.However,the neighborhood covering model has the problem of low efficiency and lack of related research work.To solve this problem,triangle inequality between distances is introduced to improve the efficiency of constructing neighborhood.Meanwhile,local neighborhood covering is defined.The local strategy is used to improve the efficiency of constructing neighborhood covering.In summary,to improve the efficiency,traditional neighborhood covering model is improved from two perspectives,and a neighborhood covering model based on triangle inequality check and local strategy (TI-LNC) is proposed.In addition,current classification algorithms based on neighborhood covering models only classify samples based on neighborhood centers and neighborhood radius,and ignore the sample information in neighborhoods,which affects classification accuracy.To improve the classification accuracy of the neighborhood covering model,the consideration of sample information in the neighborhood is added,and a new classification algorithm based on TI-LNC is designed.The experimental results on 10 UCI data sets show that the proposed model which is reasonable and effective can achieve higher efficiency and better classification accuracy.

Key words: Neighborhood rough set, Neighborhood covering model, Local neighborhood covering, Triangle inequality check

CLC Number: 

  • TP391.9
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