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A Weighted Approach for Class Association Rules

  • Loan T. T. Nguyen
  • Bay VoEmail author
  • Thang Mai
  • Thanh-Long Nguyen
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 769)

Abstract

Class association rule mining is one of the most important studies supporting classification and prediction. Multiple researches recently focus on mining class association rules using support and confidence user-defined thresholds. However, in the real datasets, each attribute is associated with an indicator value. Based on the actual needs, in this paper, we propose a new approach which combines support, confidence and an interestingness measure (weight) to quickly improve the accuracy of class association rules.

Keywords

Classification Class association rules Data mining 

Notes

Acknowledgements

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.05-2015.10.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Loan T. T. Nguyen
    • 1
    • 2
  • Bay Vo
    • 3
    Email author
  • Thang Mai
    • 4
  • Thanh-Long Nguyen
    • 5
    • 6
  1. 1.Division of Knowledge and System Engineering for ICTTon Duc Thang UniversityHo Chi Minh CityVietnam
  2. 2.Faculty of Information TechnologyTon Duc Thang UniversityHo Chi Minh CityVietnam
  3. 3.Faculty of Information TechnologyHo Chi Minh City University of TechnologyHo Chi Minh CityVietnam
  4. 4.Software Development DepartmentNashTech GlobalHo Chi Minh CityVietnam
  5. 5.Center for Information TechnologyHo Chi Minh City University of Food IndustryHo Chi Minh CityVietnam
  6. 6.VŠB-Technical University of OstravaOstrava-PorubaCzech Republic

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