The Present Situation and Development Tendency of Classification Based on Negative Association Rules

摘要：

One application of association rule mining (ARM) is to identify classification association rules (CARs) that can be used to classify future instances from the same population as the data being mined.Associative classification is a well-known technique which uses association rules to predict the class label for new data object.This model has been recently reported to achieve higher accuracy than traditional classification approaches like C4.5.Only limits in view of positive association rules used in classification.This paper introduces main methods and the present situation of classification based on association rules,expatiates the present situation and main technologies of negative association rules,introduces the problem of exploding frequent itemsets and points out the development tendency of classification based on negative association rules.

关键词： Negative Association Rules Classification Method Frequent Negative Itemsets

作者: Long Zhao Xiangjun Dong Runian Geng He Jiang

作者单位: School of Information Science and Technology,Shandong Institute of Light Industry,Jinan 250353,P.R.C School of Information Science and Technology,Shandong Institute of Light Industry,Jinan 250353,P.R.C

会议类型: 国际会议

会议名称: 2008年国际电子商务、工程及科学领域的分布式计算和应用学术研讨会(2008 International Symposium on Distributed Computing and Applications for Business Engineering and Science)

会议地点: 大连

会议语种:英文

页码: 442-447

在线出版日期: 2008-07-27（万方平台首次上网日期，不代表论文的发表时间）