摘要
粗糙集理论在对不精确、不确定和不完全的数据进行分类分析和知识获取中具有突出的优势。属性约简是粗糙集理论中的一个核心问题。由定义计算约简是一个典型的NP问题。本文对粗糙集理论进行阐述,在此基础上提出了一个基于条件熵的启发式属性约简算法。并通过实例表明该方法是可行和有效的。
Rough set theory is an effective approach to imprecision,vagueness,and incompleteness in classification analysis and knowledge discovery .Attribute reduction is a key problem for rough set theory.while computing reduction according to the definitions directly is a typical NP problem.In this paper, Basic concept of rough set theory is presented,one heuristic algorithm for attribution reduction based on conditional entropy is proposed.The actual application shows that the method is feasible and effective.
出处
《微计算机信息》
2010年第18期212-213,149,共3页
Control & Automation
关键词
粗糙集
属性约简
决策表
差别矩阵
信息熵
Rough set
Attribute reduction
Decision table
Discernibility matrix
Information entropy
