摘要
关联规则是数据挖掘的重要模式之一,有着极其重要的应用价值,但是传统的基于支持度-置信度框架的关联规则挖掘算法在实际应用中存在诸多不足。引入相关性分析,设计了一种基于遗传算法的正相关关联规则挖掘算法。最后,将该算法应用于名老中医临证经验分析挖掘的实际问题,实验证明,它能有效地弥补传统关联规则挖掘算法的不足。
Association rule is one of the important modes in data mining and has a very important value.However,the traditional algorithms of association rules which are based on support and confidence framework have lots of limitation in practical applications.A new algorithm for mining positively correlated association rules based on genetic algorithms is designed.Finally,the algorithm is applied to the mining and analysis of clinical experience of famous herbalist doctors.Experimental results show that the new method can remedy the deficiency of traditional association rules algorithm.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第6期227-230,共4页
Computer Engineering and Applications
基金
国家"十一五"科技支撑计划(No.2007BAI10B06)
the National Project of Scientific and Technical Supporting Programs Funded by Ministry of Science & Technology of China During the 11th Five-year Plan.No.2007BAI10B06
关键词
数据挖掘
关联规则
遗传算法
相关分析
data mining
association rules
genetic algorithms
correlated calculation
