A multiobjective GRASP for rule selection

Alan P. Reynolds, David W. Corne, Beatriz De La Iglesia

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

7 Citations (Scopus)

Abstract

This paper describes the application of a multiobjective GRASP to rule selection, where previously generated simple rules are combined to give rule sets that minimize complexity and misclassfication cost. As rule selection performance depends heavily on the diversity and quality of the previously generated rules, this paper also investigates a range of multiobjective approaches for creating this initial rule set and the effect on the quality of the resulting classifier. Copyright 2009 ACM.

Original languageEnglish
Title of host publicationProceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Pages643-650
Number of pages8
DOIs
Publication statusPublished - 2009
Event11th Annual Genetic and Evolutionary Computation Conference - Montreal, QC, Canada
Duration: 8 Jul 200912 Jul 2009

Conference

Conference11th Annual Genetic and Evolutionary Computation Conference
Abbreviated titleGECCO-2009
CountryCanada
CityMontreal, QC
Period8/07/0912/07/09

Keywords

  • Data mining
  • GRASP
  • Multiobjective optimization
  • Rule induction
  • Rule selection

Fingerprint Dive into the research topics of 'A multiobjective GRASP for rule selection'. Together they form a unique fingerprint.

  • Cite this

    Reynolds, A. P., Corne, D. W., & De La Iglesia, B. (2009). A multiobjective GRASP for rule selection. In Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 (pp. 643-650) https://doi.org/10.1145/1569901.1569990