Improving the Performance of Association Classifiers by Rule Prioritization

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 期刊論文 > Item 987654321/92498

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题名:	Improving the Performance of Association Classifiers by Rule Prioritization
作者:	Chen, Chun-Hao;Chiang, Rui-Dong;Lee, Cho-Ming;Chen, Chih-Yang
贡献者:	淡江大學資訊工程學系
关键词:	Associative classification algorithm;Association rule;Ranking;Rule prioritization;Rule dependence
日期:	2012-12-01
上传时间:	2013-10-16 15:42:12 (UTC+8)
出版者:	Amsterdam: Elsevier BV
摘要:	Numerous associative classification algorithms have been proposed but none considers the rule dependence problem, which directly influences the classification accuracy. Since finding the optimal execution order of class association rules (CARs) is a combinatorial problem, this study proposes a polynomial-time algorithm that re-ranks the execution order of CARs by rule priority to reduce the influence of rule dependence. The classification accuracy and recall rate of the associative classification algorithm are thus improved. The experimental results show that the proposed association classifier yields better classification results than those of an association classifier that does not consider rule dependence.
關聯:	Knowledge-Based Systems 36, pp.59–67
DOI:	10.1016/j.knosys.2012.06.004
显示于类别:	[資訊工程學系暨研究所] 期刊論文

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