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

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorMarcilio Jr, Wilson E. [UNESP]-
Autor(es): dc.creatorEler, Danilo M. [UNESP]-
Autor(es): dc.creatorIEEE-
Data de aceite: dc.date.accessioned2022-02-22T00:59:32Z-
Data de disponibilização: dc.date.available2022-02-22T00:59:32Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/SIBGRAPI51738.2020.00053-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/210335-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/210335-
Descrição: dc.descriptionExplainability 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.-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionFundacao de Amparo a Pesquisa do Estudo de Sao Paulo grant-
Descrição: dc.descriptionSao Paulo State Univ, Dept Math & Comp Sci, Presidente Prudente, SP, Brazil-
Descrição: dc.descriptionSao Paulo State Univ, Dept Math & Comp Sci, Presidente Prudente, SP, Brazil-
Descrição: dc.descriptionCAPES: 88887.487331/2020-00-
Descrição: dc.descriptionFundacao de Amparo a Pesquisa do Estudo de Sao Paulo grant: 2018/17881-3-
Formato: dc.format340-347-
Idioma: dc.languageen-
Publicador: dc.publisherIeee-
Relação: dc.relation2020 33rd Sibgrapi Conference On Graphics, Patterns And Images (sibgrapi 2020)-
???dc.source???: dc.sourceWeb of Science-
Título: dc.titleFrom explanations to feature selection: assessing SHAP values as feature selection mechanism-
Aparece nas coleções:Repositório Institucional - Unesp

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