dc.creator | Talbi, El-Ghazali | es |
dc.creator | Jourdan, Laetitia | es |
dc.creator | García Nieto, José Manuel | es |
dc.creator | Alba, Enrique | es |
dc.date.accessioned | 2021-05-06T08:01:43Z | |
dc.date.available | 2021-05-06T08:01:43Z | |
dc.date.issued | 2008 | |
dc.identifier.citation | Talbi, E., Jourdan, L., García Nieto, J.M. y Alba, E. (2008). Comparison of population based metaheuristics for feature selection: Application to microarray data classification. En ACS/IEEE-AICCSA 2008: International Conference on Computer Systems and Applications (45-52), Doha, Qatar: IEEE Computer Society. | |
dc.identifier.isbn | 978-1-4244-1967-8 | es |
dc.identifier.issn | 2161-5322 | es |
dc.identifier.uri | https://hdl.handle.net/11441/108612 | |
dc.description.abstract | In this work we compare the use of a Particle Swarm Optimization
(PSO) and a Genetic Algorithm (GA) (both augmented
with Support Vector Machines SVM) for the classification
of high dimensional Microarray Data. Both algorithms
are used for finding small samples of informative
genes amongst thousands of them. A SVM classifier with
10-fold cross-validation is applied in order to validate and
evaluate the provided solutions. A first contribution is to
prove that PSOSVM is able to find interesting genes and
to provide classification competitive performance. Specifically,
a new version of PSO, called Geometric PSO, is empirically
evaluated for the first time in this work. In this
sense, a comparison of this approach with a new GASVM
and also with other existing methods of literature is provided.
A second important contribution consists in the actual
discovery of new and challenging results on six public
datasets identifying significant in the development of a variety
of cancers (leukemia, breast, colon, ovarian, prostate,
and lung). | es |
dc.format | application/pdf | es |
dc.format.extent | 8 | es |
dc.language.iso | eng | es |
dc.publisher | IEEE Computer Society | es |
dc.relation.ispartof | ACS/IEEE-AICCSA 2008: International Conference on Computer Systems and Applications (2008), pp. 45-52. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Comparison of population based metaheuristics for feature selection: Application to microarray data classification | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/4493515 | es |
dc.identifier.doi | 10.1109/AICCSA.2008.4493515 | es |
dc.publication.initialPage | 45 | es |
dc.publication.endPage | 52 | es |
dc.eventtitle | ACS/IEEE-AICCSA 2008: International Conference on Computer Systems and Applications | es |
dc.eventinstitution | Doha, Qatar | es |
dc.relation.publicationplace | New York, USA | es |