Rough Sets and Three-Way Decisions

被引:76
作者
Yao, Yiyu [1 ]
机构
[1] Univ Regina, Dept Comp Sci, Regina, SK S4S 0A2, Canada
来源
ROUGH SETS AND KNOWLEDGE TECHNOLOGY, RSKT 2015 | 2015年 / 9436卷
关键词
MODEL;
D O I
10.1007/978-3-319-25754-9_6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The notion of three-way decisions was originally introduced by the needs to explain the three regions of probabilistic rough sets. Recent studies show that rough set theory is only one of possible ways to construct three regions. A more general theory of three-way decisions has been proposed, embracing ideas from rough sets, interval sets, shadowed sets, three-way approximations of fuzzy sets, orthopairs, square of oppositions, and others. This paper presents a trisecting-and-acting framework of three-way decisions. With respect to trisecting, we divide a universal set into three regions. With respect to acting, we design most effective strategies for processing the three regions. The identification and explicit investigation of different strategies for different regions are a distinguishing feature of three-way decisions.
引用
收藏
页码:62 / 73
页数:12
相关论文
共 48 条
[1]  
[Anonymous], 2015, INT J MACH LEARN CYB, P1
[2]  
Chellas B. F., 1980, Modal Logic: An Introduction
[3]  
Ciucci Davide, 2012, Rough Sets and Knowledge Technology. Proceedings of the 7th International Conference, RSKT 2012, P504, DOI 10.1007/978-3-642-31900-6_62
[4]   Borderline vs. unknown: comparing three-valued representations of imperfect information [J].
Ciucci, Davide ;
Dubois, Didier ;
Lawry, Jonathan .
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2014, 55 (09) :1866-1889
[5]  
Ciucci D, 2014, LECT NOTES COMPUT SC, V8536, P1, DOI 10.1007/978-3-319-08644-6_1
[6]   Orthopairs: A Simple and Widely Used Way to Model Uncertainty [J].
Ciucci, Davide .
FUNDAMENTA INFORMATICAE, 2011, 108 (3-4) :287-304
[7]  
Deng X. F., 2015, THESIS
[8]   Decision-theoretic three-way approximations of fuzzy sets [J].
Deng, Xiaofei ;
Yao, Yiyu .
INFORMATION SCIENCES, 2014, 279 :702-715
[9]  
Dubois D, 2012, LOG UNIVERSALIS, V6, P149, DOI 10.1007/s11787-011-0039-0
[10]   Probabilistic Rule Induction with the LERS Data Mining System [J].
Grzymala-Busse, Jerzy W. ;
Yao, Yiyu .
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2011, 26 (06) :518-539