Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (12): 54-59.DOI: 10.3778/j.issn.1002-8331.1905-0389

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Attribute Reduction on Weighted Decision Table

LI Xu, RONG Zijing, REN Yan   

  1. 1.School of Information Management, Xinjiang University of Finance & Economics, Urumqi 830012, China
    2.School of Information Science, Beijing Language and Culture University, Beijing 100083, China
  • Online:2020-06-15 Published:2020-06-09



  1. 1.新疆财经大学 信息管理学院,乌鲁木齐 830012
    2.北京语言大学 信息科学学院,北京 100083


Attribute reduction is an important part in rough set theory. For the usual decision table, when considering each row in the table as a decision rule, the number of occurrences of the same decision rule is taken as the weight, and thus the weighted decision table is obtained. The corresponding matrix of positive region reduction is proposed and the proof is given, and the algorithm 1 is obtained. Comparing the positive region reduction algorithm between the decision table and the weighted decision table, it is found that the algorithm 1 is superior to the former to some extent after converting the decision table into a weighted decision table. Then the corresponding matrix of approximate classification accuracy reduction is proposed and proved. Two algorithms are tested on the selected UCI datasets. The feasibility and effectiveness of the proposed algorithm are illustrated by experiments.

Key words: rough set, attribute reduction, weighted decision table, positive region reduction, approximate classification accuracy reduction



关键词: 粗糙集, 属性约简, 带权决策表, 正域约简, 近似分类精度约简