摘要
粗集理论是一种处理不确定、不一致数据的新的数学工具。属性约简是粗集理论研究的重要内容,是在保持信息系统分类能力不变的基础上,删除冗余属性。而求取最优约简是一个NP难题,为了能够有效地获取信息系统的约简,提出一种改进算法。该算法以知识量作为启发式信息,每次删除知识量小的属性,直到找到约简为止。分析及实例表明此算法具有有效性。
Rough set （RS） theory is a new mathematical tool to deal with knowledge, particularly when knowledge is imprecise or inconsistent. Attribute reduction is one of the important issues of rough set theory and its application range is extensive. It is to remove superfluous knowledge from information systems while preserving the consistency of classification. However, it has been proved that finding the best reduction is the NP-hard problem. For the purpose of getting the reduction of systems effectively, an improved algorithm is put forward, The algorithm which takes knowledge magnitude as the heuristic information, and deletes the attribute which contains small knowledge magnitude till getting the reduction. The analysis and experiment show that this algorithm is effective.
出处
《计算机工程与设计》
CSCD
北大核心
2008年第13期3432-3434,共3页
Computer Engineering and Design
关键词
粗集理论
属性约简
知识量
启发式信息
算法
rough set theory
attribute reduction
knowledge magnitude
heuristic information
algorithm
