Computer Science ›› 2018, Vol. 45 ›› Issue (10): 229-234.doi: 10.11896/j.issn.1002-137X.2018.10.042

• Artificial Intelligence • Previous Articles     Next Articles

Attribute Reduction Based on Concentration Boolean Matrix under Dominance Relations

LI Yan, GUO Na-na, WU Ting-ting, ZHAN Yan   

  1. Key Lab of Machine Learning and Computational Intelligence,College of Mathematics and Information Science, Hebei University,Baoding,Hebei 071002,China
  • Received:2017-08-16 Online:2018-11-05 Published:2018-11-05

Abstract: Under the framework of dominance relation-based rough set approach (DRSA),attribute reduction was stu-died for inconsistent target information systems.The methods based on dominance matrix are the most commonly used ones,but not all elements in the matrix are valid.The concentration dominance matrix only preserves the smallest set of attributes which are useful for attribute reduction,and thus the computational complexity can be significantly reduced.On the other side,the concentration Boolean matrix further improves the generation efficiency of the dominance matrix by Boolean algebra.This paper extended the concentration Boolean matrix method under equivalence relations to that under dominance relations.The concept of concentration Boolean matrix was proposed for the dominance matrix,and the corresponding efficient reduction method was established to improve the efficiency of the reduction algorithm.Finally,nine UCI data sets were used in the experiments,and the results show the feasibility and effectiveness of the proposed method.

Key words: Attribute reduction, Concentration boolean matrix, Concentration dominance matrix, Dominance relation, Rough set

CLC Number: 

  • TP181
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