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Data mining using contrast-sets: A comparative study

  • Author / Creator
    Satsangi, Amit
  • Comparative analysis is an essential part of understanding how and why things work the way they do. Why postgraduate degree holders really earn more money than those with an undergraduate degree? What factors contribute to pre-term births? Why are some students more successful than others? The above questions require comparison between various classes. Contrast-set mining was first proposed as a way to identify attributes that significantly differentiate between various classes (groups). While contrast-set mining has been widely applied for differentiating between different groups however, no clear picture seems to have emerged regarding how to extract the contrast-sets that discriminate most between the classes. In this thesis we try to address the problem of finding meaningful contrast sets by applying Association Rule Mining. We report a new family of contrast-sets, and we present and compare the results of our experiments with the well known algorithm for contrast-set mining - STUCCO.

  • Subjects / Keywords
  • Graduation date
    2011-06
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3M942
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Zaiane, Osmar (Computing Science)
  • Examining committee members and their departments
    • Miller, James (Electrical and Computer Engineering)
    • Ray, Nilanjan (Computing Science)