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Filtros : "Data Mining and Knowledge Discovery" "Estados Unidos" Limpar

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Artigo de periodico
Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm (2024)
Raimundo, Marcos M ; Nonato, Luis Gustavo ; Poco, Jorge
Source: Data Mining and Knowledge Discovery. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RAIMUNDO, Marcos M e NONATO, Luis Gustavo e POCO, Jorge. Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm. Data Mining and Knowledge Discovery, v. 38, p. 2942-2974, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10618-022-00906-4. Acesso em: 11 nov. 2025.
APA
Raimundo, M. M., Nonato, L. G., & Poco, J. (2024). Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm. Data Mining and Knowledge Discovery, 38, 2942-2974. doi:10.1007/s10618-022-00906-4
NLM
Raimundo MM, Nonato LG, Poco J. Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38 2942-2974.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1007/s10618-022-00906-4
Vancouver
Raimundo MM, Nonato LG, Poco J. Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38 2942-2974.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1007/s10618-022-00906-4
Artigo de periodico
Ensembles of label noise filters: a ranking approach (2016)
Garcia, Luís P. F; Lorena, Ana C; Matwin, Stan; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Data Mining and Knowledge Discovery. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GARCIA, Luís P. F et al. Ensembles of label noise filters: a ranking approach. Data Mining and Knowledge Discovery, v. 30, n. 5, p. 1192-1216, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10618-016-0475-9. Acesso em: 11 nov. 2025.
APA
Garcia, L. P. F., Lorena, A. C., Matwin, S., & Carvalho, A. C. P. de L. F. de. (2016). Ensembles of label noise filters: a ranking approach. Data Mining and Knowledge Discovery, 30( 5), 1192-1216. doi:10.1007/s10618-016-0475-9
NLM
Garcia LPF, Lorena AC, Matwin S, Carvalho ACP de LF de. Ensembles of label noise filters: a ranking approach [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 5): 1192-1216.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1007/s10618-016-0475-9
Vancouver
Garcia LPF, Lorena AC, Matwin S, Carvalho ACP de LF de. Ensembles of label noise filters: a ranking approach [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 5): 1192-1216.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1007/s10618-016-0475-9

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