AN APPROACH FOR ATTRIBUTE REDUCTION IN SET-VALUED ORDERED INFORMATION SYSTEMS BASED ON INFORMATION ENTROPY

被引：0
|
作者：
Luo, Chuan [1 ]
Li, Tianrui [1 ]
Chen, Hongmei [1 ]
Zhang, Junbo [1 ]
机构：
[1] Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 610031, Peoples R China
来源：
UNCERTAINTY MODELING IN KNOWLEDGE ENGINEERING AND DECISION MAKING | 2012年 / 7卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Rough sets theory is an important mathematic tool for data mining. Feature selection is a main step in the course of data mining. In this paper, we focus on the attribute reduction by using rough set theory in Set-valued Ordered Information Systems (SOIS) from the view of information theory. Firstly, we introduce the information entropy and relative information quantity to SOIS. Then, we define attribute reduction by means of information entropy. Furthermore, an algorithm for computing reducts is proposed based on the information entropy. Finally, an illustrative example is employed to show the effectiveness of the proposed method for attribute reduction in SOIS.
引用
收藏
页码：975 / 980
页数：6
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