Record-to-Record Travel algorithm for attribute reduction in rough set theory

Majdi Mafarja, Salwani Abdullah

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Attribute reduction is the process of selecting a minimal attribute subset from a problem domain while retaining a suitably high accuracy in representing the original attributes. In this work, we propose a new attribute reduction algorithm called record-to-record travel (RRT) algorithm and employ a rough set theory as a mathematical tool to evaluate the quality of the obtained solutions. RRT is an optimization algorithm that is inspired from simulated annealing, which depends on a single parameter called DEVIATION. Experimental results on 13 well known UCI datasets show that the proposed method, coded as RRTAR, is comparable with other rough set-based attribute reduction methods available in the literature.

Original languageEnglish
Pages (from-to)507-513
Number of pages7
JournalJournal of Theoretical and Applied Information Technology
Volume49
Issue number2
Publication statusPublished - 2013

Fingerprint

Attribute Reduction
Rough set theory
Rough Set Theory
Attribute
Reduction Method
Simulated annealing
Rough Set
Simulated Annealing
Optimization Algorithm
High Accuracy
Subset
Evaluate
Experimental Results

Keywords

  • Attribute reduction
  • Record-to-Record Travel algorithm
  • Rough set theory

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Record-to-Record Travel algorithm for attribute reduction in rough set theory. / Mafarja, Majdi; Abdullah, Salwani.

In: Journal of Theoretical and Applied Information Technology, Vol. 49, No. 2, 2013, p. 507-513.

Research output: Contribution to journalArticle

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