[1]YIN Jiliang,ZHANG Nan,TONG Xiangrong,et al.Maximum distribution reduction in inconsistent interval-valued decision systems[J].CAAI Transactions on Intelligent Systems,2018,13(3):469-478.[doi:10.11992/tis.201710011]
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Maximum distribution reduction in inconsistent interval-valued decision systems

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 3 Page number: 469-478 Column: 学术论文—人工智能基础 Public date: 2018-05-05
Title:
Maximum distribution reduction in inconsistent interval-valued decision systems
Author(s):
YIN Jiliang1; 2;  ZHANG Nan1; 2;  TONG Xiangrong1; 2;  CHEN Manru1; 2
1. Key Lab for Data Science and Intelligence Technology of Shandong Higher Education Institutes, Yantai University, Yantai 264005, China;
2. School of Computer and Control Engineering, Yantai University, Yantai 264005, China
Keywords:
distributed reduction; maximum distributed reduction; confidence coefficient; compatibility relation; discernibility matrix; inharmonious; interval-valued; decision system
CLC:
TP181
DOI:
10.11992/tis.201710011
Abstract:
Distribution reduction is one of the important methods of attribute reduction as it can guarantee consistent confidence coefficients of all decision rules before and after reduction. Maximum distributed reduction keeps the unchanged rule with the highest confidence coefficient in the decision system, and extracting a rule with a high confidence coefficient has a wide application value. This paper introduces the concept of maximum confidence coefficient for inconsistent interval-valued decision systems based on compatibility relation and proposes a maximum distribution reduction algorithm based on discernibility matrix, whereby a discernibility matrix is constructed to keep the unchanged maximum distribution. The relationship between the maximum distribution reduction algorithm in inconsistent interval-valued decision systems and other reduction algorithms was analyzed. Experiments were performed using UCI standard data sets, and the proposed algorithm proved to be effective.
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