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Filtros : "Journal of Information and Data Management - JIDM" "INTELIGÊNCIA ARTIFICIAL" Removido: "MINERAÇÃO DE DADOS" Limpar

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  • Artigo de periodico

    Better initialization heuristics for order-based bayesian network structure learning (2016)

    Urcia, Walter Perez; Mauá, Denis Deratani

    Source: Journal of Information and Data Management - JIDM. Unidade: IME

    Assunto: INTELIGÊNCIA ARTIFICIAL

    How to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      URCIA, Walter Perez e MAUÁ, Denis Deratani. Better initialization heuristics for order-based bayesian network structure learning. Journal of Information and Data Management - JIDM, v. 7, n. 2, p. 181-195, 2016Tradução . . Acesso em: 23 nov. 2025.

    • APA

      Urcia, W. P., & Mauá, D. D. (2016). Better initialization heuristics for order-based bayesian network structure learning. Journal of Information and Data Management - JIDM, 7( 2), 181-195.

    • NLM

      Urcia WP, Mauá DD. Better initialization heuristics for order-based bayesian network structure learning. Journal of Information and Data Management - JIDM. 2016 ; 7( 2): 181-195.[citado 2025 nov. 23 ]

    • Vancouver

      Urcia WP, Mauá DD. Better initialization heuristics for order-based bayesian network structure learning. Journal of Information and Data Management - JIDM. 2016 ; 7( 2): 181-195.[citado 2025 nov. 23 ]

  • Trabalho de evento-anais periodico

    Hierarchical bottom-up safe semi-supervised support vector machines for multi-class transductive learning (2013)

    Covões, Thiago F; Barros, Rodrigo C; Silva, Tiago S. da; Hruschka, Eduardo Raul ; Carvalho, André Carlos Ponce de Leon Ferreira de

    Source: Journal of Information and Data Management - JIDM. Conference titles: Brazilian Symposium on Databases - SBBD. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

    Acesso à fonteHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      COVÕES, Thiago F et al. Hierarchical bottom-up safe semi-supervised support vector machines for multi-class transductive learning. Journal of Information and Data Management - JIDM. Porto Alegre: SBC. Disponível em: http://seer.lcc.ufmg.br/index.php/jidm/article/view/256. Acesso em: 23 nov. 2025. , 2013

    • APA

      Covões, T. F., Barros, R. C., Silva, T. S. da, Hruschka, E. R., & Carvalho, A. C. P. de L. F. de. (2013). Hierarchical bottom-up safe semi-supervised support vector machines for multi-class transductive learning. Journal of Information and Data Management - JIDM. Porto Alegre: SBC. Recuperado de http://seer.lcc.ufmg.br/index.php/jidm/article/view/256

    • NLM

      Covões TF, Barros RC, Silva TS da, Hruschka ER, Carvalho ACP de LF de. Hierarchical bottom-up safe semi-supervised support vector machines for multi-class transductive learning [Internet]. Journal of Information and Data Management - JIDM. 2013 ; 4( 3): 357-372.[citado 2025 nov. 23 ] Available from: http://seer.lcc.ufmg.br/index.php/jidm/article/view/256

    • Vancouver

      Covões TF, Barros RC, Silva TS da, Hruschka ER, Carvalho ACP de LF de. Hierarchical bottom-up safe semi-supervised support vector machines for multi-class transductive learning [Internet]. Journal of Information and Data Management - JIDM. 2013 ; 4( 3): 357-372.[citado 2025 nov. 23 ] Available from: http://seer.lcc.ufmg.br/index.php/jidm/article/view/256
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