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From explanations to feature selection: assessing SHAP values as feature selection mechanism

dc.contributor.authorMarcilio Jr, Wilson E. [UNESP]
dc.contributor.authorEler, Danilo M. [UNESP]
dc.contributor.authorIEEE
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2021-06-25T15:05:15Z
dc.date.available2021-06-25T15:05:15Z
dc.date.issued2020-01-01
dc.description.abstractExplainability has become one of the most discussed topics in machine learning research in recent years, and although a lot of methodologies that try to provide explanations to black-box models have been proposed to address such an issue, little discussion has been made on the pre-processing steps involving the pipeline of development of machine learning solutions, such as feature selection. In this work, we evaluate a game-theoretic approach used to explain the output of any machine learning model, SHAP, as a feature selection mechanism. In the experiments, we show that besides being able to explain the decisions of a model, it achieves better results than three commonly used feature selection algorithms.en
dc.description.affiliationSao Paulo State Univ, Dept Math & Comp Sci, Presidente Prudente, SP, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Math & Comp Sci, Presidente Prudente, SP, Brazil
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipFundacao de Amparo a Pesquisa do Estudo de Sao Paulo grant
dc.description.sponsorshipIdCAPES: 88887.487331/2020-00
dc.description.sponsorshipIdFundacao de Amparo a Pesquisa do Estudo de Sao Paulo grant: 2018/17881-3
dc.format.extent340-347
dc.identifierhttp://dx.doi.org/10.1109/SIBGRAPI51738.2020.00053
dc.identifier.citation2020 33rd Sibgrapi Conference On Graphics, Patterns And Images (sibgrapi 2020). New York: Ieee, p. 340-347, 2020.
dc.identifier.doi10.1109/SIBGRAPI51738.2020.00053
dc.identifier.issn1530-1834
dc.identifier.urihttp://hdl.handle.net/11449/210335
dc.identifier.wosWOS:000651203300045
dc.language.isoeng
dc.publisherIeee
dc.relation.ispartof2020 33rd Sibgrapi Conference On Graphics, Patterns And Images (sibgrapi 2020)
dc.sourceWeb of Science
dc.titleFrom explanations to feature selection: assessing SHAP values as feature selection mechanismen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee
unesp.departmentMatemática e Computação - FCTpt

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