J4

• 计算机科学 • 上一篇    下一篇

基于粗糙集和证据理论的决策规则提取

孙艳胜, 袁福宇, 于卓尔, 王建宇, 路 楠, 周春光   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2006-09-14 修回日期:1900-01-01 出版日期:2007-07-26 发布日期:2007-07-26
  • 通讯作者: 周春光

Extraction of Decision Rules Based on Rough Set and Evidence Theory

SUN Yansheng, YUAN Fuyu, YU Zhuoer, WANG Jianyu, LU Nan, ZHOU Chunguang   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2006-09-14 Revised:1900-01-01 Online:2007-07-26 Published:2007-07-26
  • Contact: ZHOU Chunguang

摘要: 提出一种基于粗糙集和证据理论的两阶段决策规则提取算法, 该算法首先利用粗糙集中属性缩减的思想, 找出每条规则中的重要条件属性集合, 然后再基于证据理论中证据结合的思想进一步去掉重要条件属性集中的冗余条件属性, 从而得到最终的决策规则. 所给算法简化了属性集的约简, 对高维数据也是可行的. 实验结果表明, 利用该算法能够挖掘出高质量的决策规则.

关键词: 粗糙集理论, 证据理论, 决策规则提取

Abstract: This paper presents a twophase algorithm for extraction of decision rules based on rough set and evidence theory. In the algorithm the thinking of reducing feature of rough set theory was used to get the important feature sets of each rule. Then on the basis of the thinking of evidence combination of evidence theorythe redundant features of the important feature sets was cut so as to get decision rules. The twophase algorithm presented in this paper simplifies the reducing of feature sets. And it is feasible for high dimensional data. The result of experiment shows that it can get fine decision rules.

Key words: rough set, evidence theory, extraction of decision rule

中图分类号: 

  • TP18