From explanations to feature selection: assessing SHAP values as feature selection mechanism
dc.contributor.author | Marcilio Jr, Wilson E. [UNESP] | |
dc.contributor.author | Eler, Danilo M. [UNESP] | |
dc.contributor.author | IEEE | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2021-06-25T15:05:15Z | |
dc.date.available | 2021-06-25T15:05:15Z | |
dc.date.issued | 2020-01-01 | |
dc.description.abstract | Explainability 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.affiliation | Sao Paulo State Univ, Dept Math & Comp Sci, Presidente Prudente, SP, Brazil | |
dc.description.affiliationUnesp | Sao Paulo State Univ, Dept Math & Comp Sci, Presidente Prudente, SP, Brazil | |
dc.description.sponsorship | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) | |
dc.description.sponsorship | Fundacao de Amparo a Pesquisa do Estudo de Sao Paulo grant | |
dc.description.sponsorshipId | CAPES: 88887.487331/2020-00 | |
dc.description.sponsorshipId | Fundacao de Amparo a Pesquisa do Estudo de Sao Paulo grant: 2018/17881-3 | |
dc.format.extent | 340-347 | |
dc.identifier | http://dx.doi.org/10.1109/SIBGRAPI51738.2020.00053 | |
dc.identifier.citation | 2020 33rd Sibgrapi Conference On Graphics, Patterns And Images (sibgrapi 2020). New York: Ieee, p. 340-347, 2020. | |
dc.identifier.doi | 10.1109/SIBGRAPI51738.2020.00053 | |
dc.identifier.issn | 1530-1834 | |
dc.identifier.uri | http://hdl.handle.net/11449/210335 | |
dc.identifier.wos | WOS:000651203300045 | |
dc.language.iso | eng | |
dc.publisher | Ieee | |
dc.relation.ispartof | 2020 33rd Sibgrapi Conference On Graphics, Patterns And Images (sibgrapi 2020) | |
dc.source | Web of Science | |
dc.title | From explanations to feature selection: assessing SHAP values as feature selection mechanism | en |
dc.type | Trabalho apresentado em evento | |
dcterms.license | http://www.ieee.org/publications_standards/publications/rights/rights_policies.html | |
dcterms.rightsHolder | Ieee | |
unesp.department | Matemática e Computação - FCT | pt |