期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：4
页码：1372-1377
出版社：Shri Pannalal Research Institute of Technolgy
摘要：The discovery o f association rules is an important data- mining task for which many algorithms have been proposed. However, the efficiency of these algorithms needs to be improved to handle real-world large datasets. Association rule mining often generates a huge number of rules, but a majority of them either are redundant or do not reflect the true correlation relationship among data objects. Some strong association rules are based on support and confidence can be misleading and this has been one of the major bottlenecks for successful application of association rule mining. In this paper we propose an efficient classification approach for generating intersecting association rules using dataset attributes informatio n gain and its Correlation association analysis. Experiment evaluation shows high accuracy achieved in classification in compare to existing classifiers.
