基于类FP-tree的多层关联分类器  

Multi-level Associative Classifier Based on Class FP-tree

作　　者：李琳[1] 邵峰晶[1] 杨厚俊[1] 孙仁诚[1] 

机构地区：[1]青岛大学信息工程学院,青岛266071

出　　处：《计算机科学》2011年第8期176-178,211,共4页Computer Science

基　　金：国家公益性行业科研专项(200905030);国家海洋局重点实验室开放基金课题(MA-SEG200812);山东省高等学校科技计划项目(J06G53)资助

摘　　要：针对传统多层关联分类挖掘产生大量冗余规则而影响分类效率的问题,提出了一种基于类FP-tree的多层关联分类器MACCF(Multi-level Associative Classifier based on Class FP-tree)。该分类器依据事务的类标号划分训练集,采用闭频繁模式(CLOSET+)产生完全候选项目集,通过设计适当的类内规则剪枝策略和类间规则剪枝策略,减少了大量冗余的分类规则,提高了分类的准确率;采用交叉关联规则方法,解决了交叉层数据的分类问题,实验结果表明了算法的高效性。Focused on the problem that the traditional multi-level associative classification mining cause a lot of redundancy rules which affecte the efficiency of classification,this paper presented an improved multi-level associative classifierbased on Class FP-tree named MACCF（Multi-level Associative Classifier based on Class FP-tree）.It is to plot the training set based on the class property of records,using CLOSET＋ generates to complete candidate item set,through the proposal inside and outside prune strategies reduce most of redundancy and has improved the accuracy;adopting cross associative method to solve the cross-level classification,experimental results show its high efficiency in classification.

关 键 词：数据挖掘 多层关联分类器 FP-TREE 剪枝 闭频繁模式 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]