计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (14): 163-165.

• 数据库、信号与信息处理 • 上一篇    下一篇

基于变精度粗集和搜索树的增量规则获取算法

邱兆雷1,王爱云1,陈传臻2   

  1. 1.山东师范大学 管理与经济学院,济南 250014
    2.山东师范大学 信息科学与工程学院,济南 250014
  • 收稿日期:2007-08-24 修回日期:2007-10-25 出版日期:2008-05-11 发布日期:2008-05-11
  • 通讯作者: 邱兆雷

Incremental rule-extraction algorithm based on variable precision rough set and search tree

QIU Zhao-lei1,WANG Ai-yun1,CHEN Chuan-zhen2   

  1. 1.School of Management and Economics,Shandong Normal University,Jinan 250014,China
    2.School of Information Science and Engineering,Shandong Normal University,Jinan 250014,China
  • Received:2007-08-24 Revised:2007-10-25 Online:2008-05-11 Published:2008-05-11
  • Contact: QIU Zhao-lei

摘要: 基于可变精度粗糙集模型和搜索树提出了一种新的增量式规则获取算法。该算法引入可变精度粗糙集模型以已获取规则集为启发信息,通过对解空间进行深度优先启发式搜索产生新的不确定性规则;并通过对原有规则置信度的更新,给出了原有规则集的更新算法;最后给出了实例分析。

关键词: 可变精度粗糙集, 规则获取, 搜索树, 深度优先启发式搜索算法

Abstract: The incremental rules extraction is a focus problem of KDD.A novel rule extraction algorithm which is called “RDBVPRST”(Rule Derivation Based on Variable Precision Rough Set and Search Tree)is proposed.It is one kind of depth first heuristic search algorithms.Based on this algorithm,the new rules are extracted and the current rule set is updated by updating the rules' confidence degree.At last,an example is given to illustrate the characteristics of this new incremental algorithm.

Key words: variable precision rough set, rule derivation, search tree, depth first heuristic search algorithm