摘要
基于序信息系统的知识粗糙熵,在系统中引入属性重要性的概念,利用该测度能度量序信息系统中属性集的不确定性,基于此,提出序信息系统中基于知识粗糙熵的启发式约简算法。通过实例对该方法的有效性进行检验,结果显示该算法可以作为一种有效的数据挖掘工具,为序信息系统的知识发现提供理论基础。
A definition of attribute significance is proposed based on knowledge rough entropy in ordered information systems, and important properties are obtained. It can be found that using the definition can measure uncertainty of an attribute set in the ordered information systems. A heuristic algorithm for attributes reduction is acquired in the systems. An example illustrates the validity of this algorithm, and results show that the algorithm is an efficient tool for data mining, and provides an important theoretical basis for knowledge discovery in ordered information systems.
出处
《计算机工程》
CAS
CSCD
北大核心
2010年第17期69-71,共3页
Computer Engineering
基金
重庆市教委科学技术研究基金资助项目"优势关系下信息系统知识获取的方法研究"(KJ090612)
重庆市九龙坡区科学计划研究基金资助项目"粒计算理论及其在农作物疾病预防中的应用研究"(2008Q98)
关键词
粗糙集
信息系统
优势关系
启发式算法
rough set
information system
dominance relation
heuristic algorithm
