A stable hybrid method for feature subset selection using particle swarm optimization with local search

Hassen Dhrif, Miroslav Kubat, Luis G.S. Giraldo, Stefan Wuchty

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

2 Scopus citations

Abstract

The determination of a small set of biomarkers to make a diagnostic call can be formulated as a feature subset selection (FSS) problem to find a small set of genes with high relevance for the underlying classification task and low mutual redundancy. However, repeated application of a heuristic, evolutionary FSS technique usually fails to produce consistent results. Here, we introduce COMB-PSO-LS, a novel hybrid (wrapper-filter) FSS algorithm based on Particle Swarm Optimization (PSO) that features a local search strategy to select the least dependent and most relevant feature subsets. In particular, we employ a Randomized Dependence Coefficient (RDC)-based filter technique to guide the search process of the particle swarm, allowing the selection of highly relevant and consistent features. Classifying cancer samples through patient gene expression profiles, we found that COMB-PSO-LS provides highly stable and non-redundant gene subsets that are relevant for the classification process, outperforming standard PSO methods.

Original languageEnglish (US)
Title of host publicationGECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery, Inc
Pages13-21
Number of pages9
ISBN (Electronic)9781450361118
DOIs
StatePublished - Jul 13 2019
Event2019 Genetic and Evolutionary Computation Conference, GECCO 2019 - Prague, Czech Republic
Duration: Jul 13 2019Jul 17 2019

Publication series

NameGECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference

Conference

Conference2019 Genetic and Evolutionary Computation Conference, GECCO 2019
CountryCzech Republic
CityPrague
Period7/13/197/17/19

ASJC Scopus subject areas

  • Computational Mathematics

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  • Cite this

    Dhrif, H., Kubat, M., Giraldo, L. G. S., & Wuchty, S. (2019). A stable hybrid method for feature subset selection using particle swarm optimization with local search. In GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference (pp. 13-21). (GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference). Association for Computing Machinery, Inc. https://doi.org/10.1145/3321707.3321816