A conflict-based confidence measure for associative classification

被引:0
|
作者
Vateekul, Peerapon [1 ]
Shyu, Mei-Ling [1 ]
机构
[1] Univ Miami, Dept Elect & Comp Engn, Coral Gables, FL 33124 USA
来源
PROCEEDINGS OF THE 2008 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION | 2008年
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Associative classification has aroused significant attention recently and achieved promising results. In the rule ranking process, the confidence measure is usually used to sort the class association rules (CARs). However, it may be not good enough for a classification task due to a low discrimination power to instances in the other classes. In this paper, we propose a novel conflict-based confidence measure with an interleaving ranking strategy for re-ranking CARs in an associative classification framework, which better captures the conflict between a rule and a training data instance. In the experiments, the traditional confidence measure and our proposed conflict-based confidence measure with the interleaving ranking strategy are applied as the primary sorting criterion for CARs. The experimental results show that the proposed associative classification framework achieves promising classification accuracy with the use of the conflict-based confidence measure, particularly for an imbalanced data set.
引用
收藏
页码:256 / 261
页数:6
相关论文
共 50 条
  • [31] A Conflict-Based Search Framework for Multiobjective Multiagent Path Finding
    Ren, Zhongqiang
    Rathinam, Sivakumar
    Choset, Howie
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2023, 20 (02) : 1262 - 1274
  • [32] Conflict-based negotiation strategy for human-agent negotiation
    Mehmet Onur Keskin
    Berk Buzcu
    Reyhan Aydoğan
    Applied Intelligence, 2023, 53 : 29741 - 29757
  • [33] Conflict-based Diagnosis: Adding Uncertainty to Model-based Diagnosis
    Flesch, Ildiko
    Lucas, Peter
    van der Weide, Theo
    20TH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2007, : 380 - 385
  • [34] Distance to second cluster as a measure of classification confidence
    Mitchell, Scott W.
    Remmel, Tarmo K.
    Csillag, Ferenc
    Wulder, Michael A.
    REMOTE SENSING OF ENVIRONMENT, 2008, 112 (05) : 2615 - 2626
  • [35] Efficient conflict-based learning in an RTL circuit constraint solver
    Iyer, MK
    Parthasarathy, G
    Cheng, KT
    DESIGN, AUTOMATION AND TEST IN EUROPE CONFERENCE AND EXHIBITION, VOLS 1 AND 2, PROCEEDINGS, 2005, : 666 - 671
  • [36] A Confidence and Conflict-Based Consensus Reaching Process for Large-Scale Group Decision-Making Problems With Intuitionistic Fuzzy Representations
    Ding, Ru-Xi
    Yang, Bing
    Yang, Guo-Rui
    Li, Meng-Nan
    Wang, Xueqing
    Chiclana, Francisco
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2024, 32 (06) : 3420 - 3432
  • [37] Conflict-based approach for multi-objective process synthesis
    Li, XN
    Rong, BG
    Lahdenperä, E
    Kraslawski, A
    Nyström, L
    PROCESS SYSTEMS ENGINEERING 2003, PTS A AND B, 2003, 15 : 946 - 951
  • [38] Secure Base Priming Diminishes Conflict-Based Anger and Anxiety
    Dutton, Donald G.
    Lane, Rene A.
    Koren, Tamara
    Bartholomew, Kim
    PLOS ONE, 2016, 11 (09):
  • [39] Synthesis of reactor/separator networks by the conflict-based analysis approach
    Li, XN
    Rong, BG
    Kraslawski, A
    EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING - 12, 2002, 10 : 241 - 246
  • [40] Speech Corpus Generation Based on N-gram Confidence Measure Classification
    Koctur, Tomas
    Ondas, Stanislav
    Juhar, Jozef
    PROCEEDINGS OF 2017 INTERNATIONAL SYMPOSIUM ELMAR, 2017, : 149 - 152