粗集理论中一种决策表离散化算法  

A Discretization Algorithm for Decision Table in Rough Set Theory

作　　者：史运平[1] 

机构地区：[1]太原工业学院教务处,山西太原030008

出　　处：《机械工程与自动化》2008年第3期91-93,共3页Mechanical Engineering & Automation

摘　　要：连续属性的离散化问题是机器学习、数据挖掘等领域中的重要研究课题之一。提出一种基于粗糙集理论的决策表离散化算法,该算法是一种基于决策表属性重要性的算法。首先给出粗糙集理论的几个基本概念,如决策表、不可分辨关系、信息熵和条件熵等,然后对离散化问题进行介绍,给出了基于决策表属性重要性的粗糙集连续属性离散化算法。该算法计算简单、易于实现,并以实例加以说明。Discretization of continuous attributes is one of important problems in Machine Learning, Data Mining and the other research area. The algorithm of this paper is based on the rough set theory and the importance of condition attributes. Firstly,the paper gives some concept of rough set theory ：decision table, indiscernible relation, information entropy and condition entropy. And then discusses the problem of discretization,a discretization algorithm of continue attributes in rough set based on the importance of condition attributes is illustrated.

关 键 词：粗糙集 决策表 离散化 

分 类 号：TB11[理学—数学]