Structured approximations as a basis for three-way decisions in rough set theory

被引:67
|
作者
Hu, Mengjun [1 ]
Yao, Yiyu [1 ]
机构
[1] Univ Regina, Dept Comp Sci, Regina, SK S4S 0A2, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Three-way decision; Structured approximation; Incomplete information; Rough set; SYSTEMS;
D O I
10.1016/j.knosys.2018.11.022
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A major application of rough set theory is concept analysis for deciding if an object is an instance of a concept based on its description. Objects with the same description form an equivalence class and the family of equivalence classes is used to define rough set approximations. When deriving the decision rules from approximations, the description of an equivalence class is the left-hand-side of a decision rule. Therefore, it is useful to retain structural information of approximations, that is, the composition of an approximation in terms of equivalence classes. However, existing studies do not explicitly consider the structural information. To address this issue, we introduce structured rough set approximations in both complete and incomplete information tables, which serve as a basis for three-way decisions with rough sets. In a complete table, we define a family of conjunctively definable concepts. The structured three-way approximations are three structured positive, boundary and negative regions given by three sets of conjunctively definable concepts. By adopting a possible-world semantics, we introduce the notion of conjunctively definable interval concepts in an incomplete table, which is used to construct the structured three-way approximations. The internal structure of structured approximations contributes to sound semantics of rough set approximations and is directly and explicitly related to three-way decision rules. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:92 / 109
页数:18
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