Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (27): 114-118.

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Heuristics attribute reduction in interval-valued decision system

LIANG Chunhua1,2, ZHANG Haiyun2   

  1. 1.Department of Economical Information, Shanxi Finance & Taxation College, Taiyuan 030024, China
    2.School of Computer & Information Technology, Shanxi University, Taiyuan 030006, China
  • Online:2012-09-21 Published:2012-09-24

区间值决策信息系统的启发式属性约简

梁春华1,2,张海云2   

  1. 1.山西省财政与税务专科学校 经济信息系,太原 030024
    2.山西大学 计算机与信息技术学院,太原 030006

Abstract: Interval-valued decision information systems are generalized models of single-valued information systems. A kind of [α] maximal tolerance class is introduced by similarity grade of attribute’s interval-value in interval-valued decision system. This paper defines new conditional entropy among attributes in interval-valued information systems and proposes two types of measurement of relative attribute importance, which is inner attribute importance and outer attribute importance. Furthermore, a heuristic relative attribute reduction algorithm based on[α]conditional information entropy is given, and the validity of the algorithm is illustrated by some experiments.

Key words: interval-valued decision system, [α]maximal consistent class, [α]approximation reduction, relative attribute importance

摘要: 区间值决策信息系统是单值信息系统的一种推广,借助于属性区间值的相似程度在区间值决策系统上引入[α]极大相容类的概念,定义了一种新的条件信息熵,提出了相对属性内(外)重要度的度量方法,进一步,给出基于[α]条件信息熵的启发式相对约简算法,通过实验验证了该算法的有效性。

关键词: 区间值决策系统, [&alpha, ]极大相容类, [&alpha, ]近似约简, 相对属性重要度