摘要
首先给出t相似度的定义,并引入t相似类的概念。随后,借助研究对象的t相似类定义了相似划分算法和广义决策集,并研究它们的性质,给出基于相似划分的类对应规则提取方法。接着,给出类对应规则中各条件类的区间表达,得到了面向连续值域决策表的规则提取算法。最后,结合实例说明了决策规则提取算法的实现过程。
First, the definition of t similarity degree between objects, t similarity class, similar partition operator, generalized decision set as well as their properties are discussed. Then, a decision algorithm for decision table with continuous attributes is provided. At last, the process of obtaining decision rules from continuous value decision table is explained by an example.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2005年第6期652-656,共5页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金(No.6044023)
教育部博士点基金(No.20020027013)
教育部科学技术重点项目(No.03184)
973国家重大基础研究计划基金(No.2002CB312200)
关键词
连续值域决策表
t相似度
t相似类
相似划分算法
广义决策集
规则获取
Continuous Domain Decision Table, t Similarity Degree, t Similarity Class, Similar Partition Operator, Generalized Decision Set, Rule Obtain