淡江大學機構典藏:Item 987654321/92498
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    題名: Improving the Performance of Association Classifiers by Rule Prioritization
    作者: Chen, Chun-Hao;Chiang, Rui-Dong;Lee, Cho-Ming;Chen, Chih-Yang
    貢獻者: 淡江大學資訊工程學系
    關鍵詞: Associative classification algorithm;Association rule;Ranking;Rule prioritization;Rule dependence
    日期: 2012-12-01
    上傳時間: 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
    顯示於類別:[資訊工程學系暨研究所] 期刊論文

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