English  |  正體中文  |  简体中文  |  Items with full text/Total items : 52084/87215 (60%)
Visitors : 8913057      Online Users : 324
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/92498

    Title: Improving the Performance of Association Classifiers by Rule Prioritization
    Authors: Chen, Chun-Hao;Chiang, Rui-Dong;Lee, Cho-Ming;Chen, Chih-Yang
    Contributors: 淡江大學資訊工程學系
    Keywords: Associative classification algorithm;Association rule;Ranking;Rule prioritization;Rule dependence
    Date: 2012-12-01
    Issue Date: 2013-10-16 15:42:12 (UTC+8)
    Publisher: Amsterdam: Elsevier BV
    Abstract: 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.
    Relation: Knowledge-Based Systems 36, pp.59–67
    DOI: 10.1016/j.knosys.2012.06.004
    Appears in Collections:[資訊工程學系暨研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat
    0950-7051_36p59-67.pdf670KbAdobe PDF96View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback