关于决策表约简的CEBARKNC算法改进  

Improved CEBARKNC on decision table reduction

作　　者：李明[1] 黄文涛[1] 刘智云[1] 

机构地区：[1]兰州理工大学计算机与通信学院,甘肃兰州730050

出　　处：《计算机应用》2006年第4期864-866,共3页journal of Computer Applications

基　　金：甘肃省自然科学基金(3ZS042B25007)

摘　　要：CEBARKNC算法是基于条件信息熵的决策表约简算法,但是该算法对于某些决策表的约简是不完全的。通过对CEBARKNC算法的分析,找出该算法的约简不完全的原因,并讨论了启发信息的构造,进而在此基础上提出了以粗糙集的代数理论为基础,以条件信息熵为属性约简的启发式信息的改进算法。CEBARKNC （Conditional Entropy-Based Algorithm for Reduction of Knowledge without Computing Core） algorithm is based on conditional information entropy for reduction of decision table, but the algorithm is incomplete for some decision table. After analyzing the CEBARKNC algorithm, the reason for incomplete reduction was found, the construction of the heuristic information was discussed, and an improved algorithm which combined the algebra of the rough set theory and the conditional information entropy was put forward. The conditional information entropy was the heuristie information of the attribute reduction.

关 键 词：信息熵 约简 粗糙集 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]