摘要
实际应用中常存在缺省属性值的不完备信息系统,如何从不完备信息系统中挖掘有用规则是一个非常有价值的问题。粗糙集理论是一种有效的数据挖掘手段,但经典粗糙集缺乏对不完备信息系统的处理能力。在粗糙集拓展的基础上,设计出从不完备决策表中挖掘出有用规则的算法,并将其应用到银行贷款决策中不完备决策表的实例分析中。
Incomplete information is usually existed in real applictation, and how to mine available rules from incomplete information is a valuable problem. Rough sets theory is an effective data mining method, but classical rough sets can not deal with incomplete information system. An algorithm based on extension of classical rough sets theory for mining available rules from incomplete decision tables was provided. The algorithm applying to analyze decision of credit were also presented.
出处
《计算机工程与设计》
CSCD
北大核心
2005年第7期1767-1769,共3页
Computer Engineering and Design
基金
暨南大学自然科学基金项目(476)。
关键词
粗糙集
不完备决策表
拓展
决策规则
rough sets theory
incomplete decision tables
extension
decision rules
