Repository logo
 
Publication

Comparison of multi-objective algorithms applied to feature selection

dc.contributor.authorTürkşen, Özlem
dc.contributor.authorVieira, Susana M.
dc.contributor.authorMadeira, JFA
dc.contributor.authorApaydin, Aysen
dc.date.accessioned2017-04-26T09:02:37Z
dc.date.available2017-04-26T09:02:37Z
dc.date.issued2013
dc.description.abstractThe feature selection problem can be formulated as a multi-objective optimization (MOO) problem, as it involves the minimization of the feature subset cardinality and the misclassification error. In this chapter, a comparison of MOO algorithms applied to feature selection is presented. The used MOO methods are: Nondominated Sorting Genetic Algorithm II (NSGA-II), Archived Multi Objective Simulated Annealing (AMOSA), and Direct Multi Search (DMS). To test the feature subset solutions, Takagi- Sugeno fuzzy models are used as classifiers. To solve the feature selection problem, AMOSA was adapted to deal with discrete optimization. The multi-objective methods are applied to four benchmark datasets used in the literature and the obtained results are compared and discussed.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTÜRKSEN, Özlem; [et al] – Comparison of multi-objective algorithms applied to feature selection. Studies in Fuzziness and Soft Computing. ISSN 1434-9922. Vol. 285, (2013), pp. 359-375.pt_PT
dc.identifier.doi10.1007/978-3-642-30278-7_28pt_PT
dc.identifier.issn1434-9922
dc.identifier.urihttp://hdl.handle.net/10400.21/6939
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Verlagpt_PT
dc.titleComparison of multi-objective algorithms applied to feature selectionpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage375pt_PT
oaire.citation.startPage359pt_PT
oaire.citation.titleStudies in Fuzziness and Soft Computingpt_PT
oaire.citation.volume285pt_PT
person.familyNameTürkşen
person.familyNameMadeira
person.familyNameapaydin
person.givenNameÖzlem
person.givenNameJose Firmino Aguilar
person.givenNameaysen
person.identifier.ciencia-id6F1E-DCF0-D6EC
person.identifier.orcid0000-0002-5592-1830
person.identifier.orcid0000-0001-9523-3808
person.identifier.orcid0000-0003-4683-0459
person.identifier.ridN-6918-2016
person.identifier.scopus-author-id7003405549
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationf3bcf315-8e39-46e6-a054-fa37a36c140f
relation.isAuthorOfPublicationd495619a-a6ab-4ff5-8e70-3a1351f934dc
relation.isAuthorOfPublication197d74ae-7ca9-4122-8ec1-d9686b9b9569
relation.isAuthorOfPublication.latestForDiscoveryd495619a-a6ab-4ff5-8e70-3a1351f934dc

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Comparison_multi_objective.pdf
Size:
11.16 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: