摘要
针对海量数据挖掘过程中常见Apriori算法的弊病,提出一种基于模糊分类的Apriori优化算法。它平滑地解决了用区间划分方法处理量化属性存在的问题,避免了经典Apriori算法带来的巨大性能开销。以职称考试成绩为例,验证了该算法的有效性。
For the problems of common algorithm Apriori in massive data mining process, this paper presents an optimization algorithm Apriori based on fuzzy classification. The problems using interval approach to quantify the property division can be resovled smoothly, and huge performance overhead brought by the classic algorithm Apriori can be cut down. An example about Title Examination results has verified the validity of the algorithm.
出处
《微处理机》
2010年第4期83-85,90,共4页
Microprocessors
关键词
数据挖掘
模糊分类
优化算法
Data mining
Fuzzy classification
Optimization algorithm
