• May 03, 2016 News! IJIET Vol. 5, No. 10 has been indexed by EI (Inspec).   [Click]
  • Jun 28, 2017 News!Vol. 7, No. 9 has been indexed by Crossref.
  • Jun 22, 2017 News!Vol. 7, No. 9 issue has been published online!   [Click]
General Information
    • ISSN: 2010-3689
    • Frequency: Bimonthly (2011-2014); Monthly (Since 2015)
    • DOI: 10.18178/IJIET
    • Editor-in-Chief: Prof. Dr. Steve Thatcher
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: EI (INSPEC, IET), Electronic Journals Library, Google Scholar, Crossref and ProQuest
    • E-mail: ijiet@ejournal.net
Editor-in-chief
Prof. Dr. Steve Thatcher
University of South Australia, Australia
It is my honor to be the editor-in-chief of IJIET. The journal publishes good papers which focous on the advanced researches in the field of information and education technology. Hopefully, IJIET will become a recognized journal among the scholars in the filed of information and education technology.
IJIET 2011 Vol.1(4): 273-279 ISSN: 2010-3689
DOI: 10.7763/IJIET.2011.V1.44

Two New Heuristic Methods Based on Crisp and Fuzzy Partitions for Training Data Reduction

Tri Minh Huynh

Abstract—This paper is to introduce two heuristic methods based on crisp and fuzzy partitions for selecting the subset of instances from the training data set in high dimensional problems. This subset is called the representative training data set (RTR). A proposed genetic algorithm (GA) is used to learn a compact fuzzy rule-based system (FRBS) with the instances of RTR. RTR size is rather smaller than the initial training data set, thus time cost for learning FRBS decreases significantly. Therein the number of fuzzy rules is not only reduced but rule lengths are also shorter. The smaller size of the rule base is closely related to the interpretability of the FRBS. As a result, the final FBRS gets a suitable and acceptable balance between interpretability and accuracy.

Index Terms—Crisp partition, fuzzy partition, fuzzy rule set reduction, data reduction techniques, genetic algorithm, interpretability.

Tri Minh Huynh is with Department of Information Technology Sai Gon University Ho Chi Minh City, Viet Nam (e-mail: tri.hm@cb.sgu.edu.vn).

[PDF]

Cite: Tri Minh Huynh, "Two New Heuristic Methods Based on Crisp and Fuzzy Partitions for Training Data Reduction," International Journal of Information and Education Technology vol. 1, no. 4, pp. 273-279, 2011.

Copyright © 2008-2017. International Journal of Information and Education Technology. All rights reserved.
E-mail: ijiet@ejournal.net