Fuzzy modified great deluge algorithm for attribute reduction

Majdi Mafarja, Salwani Abdullah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

This paper proposes a local search meta-heuristic free of parameter tuning to solve the attribute reduction problem. Attribute reduction can be defined as the process of finding minimal subset of attributes from an original set with minimum loss of information. Rough set theory has been used for attribute reduction with much success. However, the reduction method inside rough set theory is applicable only to small datasets, since finding all possible reducts is a time consuming process. This motivates many researchers to find alternative approaches to solve the attribute reduction problem. The proposed method, Fuzzy Modified Great Deluge algorithm (Fuzzy-mGD), has one generic parameter which is controlled throughout the search process by using a fuzzy logic controller. Computational experiments confirmed that the FuzzymGD algorithm produces good results, with greater efficiency for attribute reduction, when compared with other meta-heuristic approaches from the literature.

Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing
PublisherSpringer Verlag
Pages195-204
Number of pages10
Volume287
ISBN (Print)9783319076911
DOIs
Publication statusPublished - 2014
Event1st International Conference on Soft Computing and Data Mining, SCDM 2014 - Parit Raja, Batu Pahat
Duration: 16 Jun 201418 Jun 2014

Publication series

NameAdvances in Intelligent Systems and Computing
Volume287
ISSN (Print)21945357

Other

Other1st International Conference on Soft Computing and Data Mining, SCDM 2014
CityParit Raja, Batu Pahat
Period16/6/1418/6/14

Fingerprint

Rough set theory
Fuzzy logic
Tuning
Controllers
Experiments

Keywords

  • Attribute Reduction
  • Fuzzy Logic
  • Great Deluge

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Mafarja, M., & Abdullah, S. (2014). Fuzzy modified great deluge algorithm for attribute reduction. In Advances in Intelligent Systems and Computing (Vol. 287, pp. 195-204). (Advances in Intelligent Systems and Computing; Vol. 287). Springer Verlag. https://doi.org/10.1007/978-3-319-07692-8_19

Fuzzy modified great deluge algorithm for attribute reduction. / Mafarja, Majdi; Abdullah, Salwani.

Advances in Intelligent Systems and Computing. Vol. 287 Springer Verlag, 2014. p. 195-204 (Advances in Intelligent Systems and Computing; Vol. 287).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mafarja, M & Abdullah, S 2014, Fuzzy modified great deluge algorithm for attribute reduction. in Advances in Intelligent Systems and Computing. vol. 287, Advances in Intelligent Systems and Computing, vol. 287, Springer Verlag, pp. 195-204, 1st International Conference on Soft Computing and Data Mining, SCDM 2014, Parit Raja, Batu Pahat, 16/6/14. https://doi.org/10.1007/978-3-319-07692-8_19
Mafarja M, Abdullah S. Fuzzy modified great deluge algorithm for attribute reduction. In Advances in Intelligent Systems and Computing. Vol. 287. Springer Verlag. 2014. p. 195-204. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-07692-8_19
Mafarja, Majdi ; Abdullah, Salwani. / Fuzzy modified great deluge algorithm for attribute reduction. Advances in Intelligent Systems and Computing. Vol. 287 Springer Verlag, 2014. pp. 195-204 (Advances in Intelligent Systems and Computing).
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