Raimundo, Marcos M 
; Nonato, Luis Gustavo ; Poco, Jorge
Source: Data Mining and Knowledge Discovery. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS
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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, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10618-022-00906-4. Acesso em: 12 jun. 2024.APA
Raimundo, M. M., Nonato, L. G., & Poco, J. (2022). Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm. Data Mining and Knowledge Discovery. doi:10.1007/s10618-022-00906-4NLM
Raimundo MM, Nonato LG, Poco J. Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm [Internet]. Data Mining and Knowledge Discovery. 2022 ;[citado 2024 jun. 12 ] Available from: https://doi.org/10.1007/s10618-022-00906-4Vancouver
Raimundo MM, Nonato LG, Poco J. Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm [Internet]. Data Mining and Knowledge Discovery. 2022 ;[citado 2024 jun. 12 ] Available from: https://doi.org/10.1007/s10618-022-00906-4
