序信息系统的启发式属性约简算法

Heuristic Attribute Reduction Algorithm to Ordered Information Systems

属性约简是粗糙集理论的核心问题之一,序信息系统中的属性约简也逐渐受到关注。基于优势类的概念,引入了序信息系统的一种信息粒度,用于度量属性集在序意义下的不确定性,进而给出了序信息系统中属性重要度的定义。在此基础上,设计了一种序信息系统的启发式属性约简算法,并通过实例分析进行了有效性检验。

Attribute reduction is one of important problems in rough set theory,and attribute reductions in ordered information systems are also concerned in recent years. We first proposed a new information granulation based on dominance classes,which can be used to measure uncertainty of an attribute set in the context of ordered information systems. Using this information granulation, a definition of attribute significance was then given in ordered information systems. At last, a heuristic reduction algorithm was put forward to ordered information systems, and the validity of this algorithm was exemplified by an illustrative example.