JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2018, Vol. 53 ›› Issue (12): 120-126.doi: 10.6040/j.issn.1671-9352.0.2017.400

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Algorithms of rule acquisition and confidence-preserved attribute reduction in covering decision systems

ZHANG Xiao1, YANG Yan-yan2   

  1. 1. School of Sciences, Xian University of Technology, Xian 710048, Shaanxi, China;
    2. Department of Automation, Tsinghua University, Beijing 100084, China
  • Online:2018-12-20 Published:2018-12-18

Abstract: The data collected in practice is of diversity. How to obtain useful knowledge from the complex data is the objective of data mining. Since covering rough sets can deal with complex data, there exists much study on the attribute reduction and rule acquisition of covering decision systems based on covering rough sets. The existing research on the rule acquisition of covering decision systems considered the confidence measure as the only evaluation criterion. However, the extracted high-confidence rules may cover fewer instances and then be potentially spurious. Therefore, a measure that can assess the coverage ability of rules is introduced, which can eliminate the chance in data and thus acquire high-confidence rules with more generalization ability. Furthermore, in order to extract compact rules, we propose a rule confidence-preserved attribute reduction heuristic algorithm.

Key words: rough sets, covering decision systems, rule acquisition, attribute reduction

CLC Number: 

  • TP18
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