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ISSN: 1549-3636 (Print)
ISSN: 1552-6607 (Online)
Research Article Open Access

PARTIAL RULE MATCH FOR FILTERING RULES IN ASSOCIATIVE CLASSIFICATION

Mohamed Hayel Refai1 and Yuhanis Yusof1
  • 1 Universiti Utara Malaysia, Malaysia

Abstract

In this study, we propose a new method to enhance the accuracy of Modified Multi-class Classification based on Association Rule (MMCAR) classifier. We introduce a Partial Rule Match Filtering (PRMF) method that allows a minimal match of the items in the rule’s body in order for the rule to be added into a classifier. Experiments on Reuters-21578 data sets are performed in order to evaluate the effectiveness of PRMF in MMCAR. Results show that the MMCAR classifier performs better as compared to the chosen competitors.

Journal of Computer Science
Volume 10 No. 4, 2014, 570-577

DOI: https://doi.org/10.3844/jcssp.2014.570.577

Submitted On: 21 August 2013 Published On: 9 December 2013

How to Cite: Refai, M. H. & Yusof, Y. (2014). PARTIAL RULE MATCH FOR FILTERING RULES IN ASSOCIATIVE CLASSIFICATION. Journal of Computer Science, 10(4), 570-577. https://doi.org/10.3844/jcssp.2014.570.577

Open AccessCopyright: © 2014 Mohamed Hayel Refai and Yuhanis Yusof. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • Modified Multi-Class Classification Based on Association Rule
  • Associative Classification
  • Text Mining