NSGA-II as feature selection technique and AdaBoost classifier for COVID-19 prediction using patient's symptoms.

Soui, Makram; Mansouri, Nesrine; Alhamad, Raed; Kessentini, Marouane; Ghedira, Khaled

Soui, Makram; Mansouri, Nesrine; Alhamad, Raed; Kessentini, Marouane; Ghedira, Khaled.

Afiliação

Soui M; College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia.
Mansouri N; University of Gabes, Gabes, Tunisia.
Alhamad R; College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia.
Kessentini M; University of Michigan - Dearborn, Dearborn, MI USA.
Ghedira K; Private Higher School of Engineering and Technology, Ariana, Tunisia.

Nonlinear Dyn ; 106(2): 1453-1475, 2021.

Article em En | MEDLINE | ID: mdl-34025034

Palavras-chave

AdaBoost; COVID-19 prediction; Feature selection; Hyper-parameters optimization; Machine learning; NSGA-II

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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