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Filtros : "Data Mining and Knowledge Discovery" "2024" 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

    Fonte: Data Mining and Knowledge Discovery. Unidade: ICMC

    Assuntos: APRENDIZADO COMPUTACIONAL, ALGORITMOS

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    • 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

    Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms (2024)

    Mantovani, Rafael Gomes ; Horváth, Tomás ; Rossi, André Luis Debiaso ; Cerri, Ricardo ; Barbon Júnior, Sylvio ; Vanschoren, Joaquin ; Carvalho, André Carlos Ponce de Leon Ferreira de

    Fonte: Data Mining and Knowledge Discovery. Unidade: ICMC

    Assuntos: APRENDIZADO COMPUTACIONAL, ALGORITMOS ÚTEIS E ESPECÍFICOS

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    • ABNT

      MANTOVANI, Rafael Gomes et al. Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. Data Mining and Knowledge Discovery, v. 38, n. 3, p. 1364-1416, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10618-024-01002-5. Acesso em: 11 nov. 2025.

    • APA

      Mantovani, R. G., Horváth, T., Rossi, A. L. D., Cerri, R., Barbon Júnior, S., Vanschoren, J., & Carvalho, A. C. P. de L. F. de. (2024). Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. Data Mining and Knowledge Discovery, 38( 3), 1364-1416. doi:10.1007/s10618-024-01002-5

    • NLM

      Mantovani RG, Horváth T, Rossi ALD, Cerri R, Barbon Júnior S, Vanschoren J, Carvalho ACP de LF de. Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38( 3): 1364-1416.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1007/s10618-024-01002-5

    • Vancouver

      Mantovani RG, Horváth T, Rossi ALD, Cerri R, Barbon Júnior S, Vanschoren J, Carvalho ACP de LF de. Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38( 3): 1364-1416.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1007/s10618-024-01002-5

  • Artigo de periodico

    Unsupervised feature based algorithms for time series extrinsic regression (2024)

    Guijo-Rubio, David ; Middlehurst, Matthew ; Arcencio, Guilherme ; Silva, Diego Furtado ; Bagnall, Anthony

    Fonte: Data Mining and Knowledge Discovery. Unidade: ICMC

    Assuntos: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, ALGORITMOS ÚTEIS E ESPECÍFICOS

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    • ABNT

      GUIJO-RUBIO, David et al. Unsupervised feature based algorithms for time series extrinsic regression. Data Mining and Knowledge Discovery, v. 38, n. 4, p. 2141-2185, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10618-024-01027-w. Acesso em: 11 nov. 2025.

    • APA

      Guijo-Rubio, D., Middlehurst, M., Arcencio, G., Silva, D. F., & Bagnall, A. (2024). Unsupervised feature based algorithms for time series extrinsic regression. Data Mining and Knowledge Discovery, 38( 4), 2141-2185. doi:10.1007/s10618-024-01027-w

    • NLM

      Guijo-Rubio D, Middlehurst M, Arcencio G, Silva DF, Bagnall A. Unsupervised feature based algorithms for time series extrinsic regression [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38( 4): 2141-2185.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1007/s10618-024-01027-w

    • Vancouver

      Guijo-Rubio D, Middlehurst M, Arcencio G, Silva DF, Bagnall A. Unsupervised feature based algorithms for time series extrinsic regression [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38( 4): 2141-2185.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1007/s10618-024-01027-w
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