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  • Source: BMC Bioinformatics. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, REDES NEURAIS, RECONHECIMENTO DE PADRÕES

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      CERRI, Ricardo et al. Reduction strategies for hierarchical multi-label classification in protein function prediction. BMC Bioinformatics, v. 17, p. 1-24, 2016Tradução . . Disponível em: https://doi.org/10.1186/s12859-016-1232-1. Acesso em: 02 out. 2024.
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      Cerri, R., Barros, R. C., Carvalho, A. C. P. de L. F. de, & Jin, Y. (2016). Reduction strategies for hierarchical multi-label classification in protein function prediction. BMC Bioinformatics, 17, 1-24. doi:10.1186/s12859-016-1232-1
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      Cerri R, Barros RC, Carvalho ACP de LF de, Jin Y. Reduction strategies for hierarchical multi-label classification in protein function prediction [Internet]. BMC Bioinformatics. 2016 ; 17 1-24.[citado 2024 out. 02 ] Available from: https://doi.org/10.1186/s12859-016-1232-1
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      Cerri R, Barros RC, Carvalho ACP de LF de, Jin Y. Reduction strategies for hierarchical multi-label classification in protein function prediction [Internet]. BMC Bioinformatics. 2016 ; 17 1-24.[citado 2024 out. 02 ] Available from: https://doi.org/10.1186/s12859-016-1232-1
  • Source: Genetic Programming and Evolvable Machines. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, COMPUTAÇÃO EVOLUTIVA, ALGORITMOS GENÉTICOS

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      BARROS, Rodrigo C e BASGALUPP, Márcio P e CARVALHO, André Carlos Ponce de Leon Ferreira de. Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification. Genetic Programming and Evolvable Machines, v. 16, n. 3, p. Se 2015, 2015Tradução . . Disponível em: https://doi.org/10.1007/s10710-014-9235-z. Acesso em: 02 out. 2024.
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      Barros, R. C., Basgalupp, M. P., & Carvalho, A. C. P. de L. F. de. (2015). Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification. Genetic Programming and Evolvable Machines, 16( 3), Se 2015. doi:10.1007/s10710-014-9235-z
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      Barros RC, Basgalupp MP, Carvalho ACP de LF de. Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification [Internet]. Genetic Programming and Evolvable Machines. 2015 ; 16( 3): Se 2015.[citado 2024 out. 02 ] Available from: https://doi.org/10.1007/s10710-014-9235-z
    • Vancouver

      Barros RC, Basgalupp MP, Carvalho ACP de LF de. Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification [Internet]. Genetic Programming and Evolvable Machines. 2015 ; 16( 3): Se 2015.[citado 2024 out. 02 ] Available from: https://doi.org/10.1007/s10710-014-9235-z
  • Source: Proceedings. Conference titles: International Joint Conference on Neural Network - IJCNN. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, REDES NEURAIS

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      CERRI, Ricardo e BARROS, Rodrigo C e CARVALHO, André Carlos Ponce de Leon Ferreira de. Hierarchical classification of gene ontology-based protein functions with neural networks. 2015, Anais.. Piscataway: IEEE, 2015. Disponível em: https://doi.org/10.1109/IJCNN.2015.7280474. Acesso em: 02 out. 2024.
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      Cerri, R., Barros, R. C., & Carvalho, A. C. P. de L. F. de. (2015). Hierarchical classification of gene ontology-based protein functions with neural networks. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN.2015.7280474
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      Cerri R, Barros RC, Carvalho ACP de LF de. Hierarchical classification of gene ontology-based protein functions with neural networks [Internet]. Proceedings. 2015 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/IJCNN.2015.7280474
    • Vancouver

      Cerri R, Barros RC, Carvalho ACP de LF de. Hierarchical classification of gene ontology-based protein functions with neural networks [Internet]. Proceedings. 2015 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/IJCNN.2015.7280474
  • Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      BARROS, Rodrigo C e CARVALHO, André Carlos Ponce de Leon Ferreira de e FREITAS, Alex A. Automatic design of decision-tree induction algorithms. . Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-14231-9. Acesso em: 02 out. 2024. , 2015
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      Barros, R. C., Carvalho, A. C. P. de L. F. de, & Freitas, A. A. (2015). Automatic design of decision-tree induction algorithms. Cham: Springer. doi:10.1007/978-3-319-14231-9
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      Barros RC, Carvalho ACP de LF de, Freitas AA. Automatic design of decision-tree induction algorithms [Internet]. 2015 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1007/978-3-319-14231-9
    • Vancouver

      Barros RC, Carvalho ACP de LF de, Freitas AA. Automatic design of decision-tree induction algorithms [Internet]. 2015 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1007/978-3-319-14231-9
  • Source: Neurocomputing. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      BARROS, Rodrigo C et al. A framework for bottom-up induction of oblique decision trees. Neurocomputing, v. 135, p. 3-12, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2013.01.067. Acesso em: 02 out. 2024.
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      Barros, R. C., Jaskowiak, P. A., Cerri, R., & Carvalho, A. C. P. de L. F. de. (2014). A framework for bottom-up induction of oblique decision trees. Neurocomputing, 135, 3-12. doi:10.1016/j.neucom.2013.01.067
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      Barros RC, Jaskowiak PA, Cerri R, Carvalho ACP de LF de. A framework for bottom-up induction of oblique decision trees [Internet]. Neurocomputing. 2014 ; 135 3-12.[citado 2024 out. 02 ] Available from: https://doi.org/10.1016/j.neucom.2013.01.067
    • Vancouver

      Barros RC, Jaskowiak PA, Cerri R, Carvalho ACP de LF de. A framework for bottom-up induction of oblique decision trees [Internet]. Neurocomputing. 2014 ; 135 3-12.[citado 2024 out. 02 ] Available from: https://doi.org/10.1016/j.neucom.2013.01.067
  • Source: Anais. Conference titles: Congresso da Sociedade Brasileira de Computação - CSBC. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      BARROS, Rodrigo C e CARVALHO, André Carlos Ponce de Leon Ferreira de e FREITAS, Alex A. On the automatic design of decision-tree induction algorithms. 2014, Anais.. Porto Alegre: SBC, 2014. Disponível em: http://csbc2014.cic.unb.br/index.php/anais-menu. Acesso em: 02 out. 2024.
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      Barros, R. C., Carvalho, A. C. P. de L. F. de, & Freitas, A. A. (2014). On the automatic design of decision-tree induction algorithms. In Anais. Porto Alegre: SBC. Recuperado de http://csbc2014.cic.unb.br/index.php/anais-menu
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      Barros RC, Carvalho ACP de LF de, Freitas AA. On the automatic design of decision-tree induction algorithms [Internet]. Anais. 2014 ;[citado 2024 out. 02 ] Available from: http://csbc2014.cic.unb.br/index.php/anais-menu
    • Vancouver

      Barros RC, Carvalho ACP de LF de, Freitas AA. On the automatic design of decision-tree induction algorithms [Internet]. Anais. 2014 ;[citado 2024 out. 02 ] Available from: http://csbc2014.cic.unb.br/index.php/anais-menu
  • Source: Proceedings. Conference titles: International Conference on Genetic and Evolutionary Computation - GECCO. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, BIOINFORMÁTICA, ALGORITMOS GENÉTICOS

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      CERRI, Ricardo et al. Evolving relational hierarchical classification rules for predicting gene ontology-based protein functions. 2014, Anais.. New York: ACM, 2014. Disponível em: https://doi.org/10.1145/2598394.2611384. Acesso em: 02 out. 2024.
    • APA

      Cerri, R., Barros, R. C., Freitas, A. A., & Carvalho, A. C. P. de L. F. de. (2014). Evolving relational hierarchical classification rules for predicting gene ontology-based protein functions. In Proceedings. New York: ACM. doi:10.1145/2598394.2611384
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      Cerri R, Barros RC, Freitas AA, Carvalho ACP de LF de. Evolving relational hierarchical classification rules for predicting gene ontology-based protein functions [Internet]. Proceedings. 2014 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1145/2598394.2611384
    • Vancouver

      Cerri R, Barros RC, Freitas AA, Carvalho ACP de LF de. Evolving relational hierarchical classification rules for predicting gene ontology-based protein functions [Internet]. Proceedings. 2014 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1145/2598394.2611384
  • Source: Information Sciences. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      BASGALUPP, Márcio P et al. Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation. Information Sciences, v. fe 2014, p. 160-181, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2013.07.025. Acesso em: 02 out. 2024.
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      Basgalupp, M. P., Barros, R. C., Carvalho, A. C. P. de L. F. de, & Freitas, A. A. (2014). Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation. Information Sciences, fe 2014, 160-181. doi:10.1016/j.ins.2013.07.025
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      Basgalupp MP, Barros RC, Carvalho ACP de LF de, Freitas AA. Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation [Internet]. Information Sciences. 2014 ; fe 2014 160-181.[citado 2024 out. 02 ] Available from: https://doi.org/10.1016/j.ins.2013.07.025
    • Vancouver

      Basgalupp MP, Barros RC, Carvalho ACP de LF de, Freitas AA. Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation [Internet]. Information Sciences. 2014 ; fe 2014 160-181.[citado 2024 out. 02 ] Available from: https://doi.org/10.1016/j.ins.2013.07.025
  • Source: IEEE Transactions on Evolutionary Computation. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      BARROS, Rodrigo C et al. Evolutionary design of decision-tree algorithms tailored to microarray gene expression data sets. IEEE Transactions on Evolutionary Computation, v. 18, n. 6, p. 873-891, 2014Tradução . . Disponível em: https://doi.org/10.1109/TEVC.2013.2291813. Acesso em: 02 out. 2024.
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      Barros, R. C., Basgalupp, M. P., Freitas, A. A., & Carvalho, A. C. P. de L. F. de. (2014). Evolutionary design of decision-tree algorithms tailored to microarray gene expression data sets. IEEE Transactions on Evolutionary Computation, 18( 6), 873-891. doi:10.1109/TEVC.2013.2291813
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      Barros RC, Basgalupp MP, Freitas AA, Carvalho ACP de LF de. Evolutionary design of decision-tree algorithms tailored to microarray gene expression data sets [Internet]. IEEE Transactions on Evolutionary Computation. 2014 ; 18( 6): 873-891.[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/TEVC.2013.2291813
    • Vancouver

      Barros RC, Basgalupp MP, Freitas AA, Carvalho ACP de LF de. Evolutionary design of decision-tree algorithms tailored to microarray gene expression data sets [Internet]. IEEE Transactions on Evolutionary Computation. 2014 ; 18( 6): 873-891.[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/TEVC.2013.2291813
  • Source: Journal of Computer and System Sciences. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CERRI, Ricardo e BARROS, Rodrigo C e CARVALHO, André Carlos Ponce de Leon Ferreira de. Hierarchical multi-label classification using local neural networks. Journal of Computer and System Sciences, v. fe 2014, n. 1, p. 39-56, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.jcss.2013.03.007. Acesso em: 02 out. 2024.
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      Cerri, R., Barros, R. C., & Carvalho, A. C. P. de L. F. de. (2014). Hierarchical multi-label classification using local neural networks. Journal of Computer and System Sciences, fe 2014( 1), 39-56. doi:10.1016/j.jcss.2013.03.007
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      Cerri R, Barros RC, Carvalho ACP de LF de. Hierarchical multi-label classification using local neural networks [Internet]. Journal of Computer and System Sciences. 2014 ; fe 2014( 1): 39-56.[citado 2024 out. 02 ] Available from: https://doi.org/10.1016/j.jcss.2013.03.007
    • Vancouver

      Cerri R, Barros RC, Carvalho ACP de LF de. Hierarchical multi-label classification using local neural networks [Internet]. Journal of Computer and System Sciences. 2014 ; fe 2014( 1): 39-56.[citado 2024 out. 02 ] Available from: https://doi.org/10.1016/j.jcss.2013.03.007
  • Source: Proceedings. Conference titles: Symposium on Applied Computing - SAC. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      BASGALUPP, Márcio P et al. Software effort prediction: a hyper-heuristic decision-tree based approach. 2013, Anais.. New York: ACM, 2013. . Acesso em: 02 out. 2024.
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      Basgalupp, M. P., Barros, R. C., Silva, T. S. da, & Carvalho, A. C. P. de L. F. de. (2013). Software effort prediction: a hyper-heuristic decision-tree based approach. In Proceedings. New York: ACM.
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      Basgalupp MP, Barros RC, Silva TS da, Carvalho ACP de LF de. Software effort prediction: a hyper-heuristic decision-tree based approach. Proceedings. 2013 ;[citado 2024 out. 02 ]
    • Vancouver

      Basgalupp MP, Barros RC, Silva TS da, Carvalho ACP de LF de. Software effort prediction: a hyper-heuristic decision-tree based approach. Proceedings. 2013 ;[citado 2024 out. 02 ]
  • Source: Evolutionary Computation. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, ALGORITMOS GENÉTICOS, APRENDIZADO COMPUTACIONAL

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      BARROS, Rodrigo C et al. Automatic design of decision-tree algorithms with evolutionary algorithms. Evolutionary Computation, v. 21, n. 4, p. 659-684, 2013Tradução . . Acesso em: 02 out. 2024.
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      Barros, R. C., Basgalupp, M. P., Carvalho, A. C. P. de L. F. de, & Freitas, A. A. (2013). Automatic design of decision-tree algorithms with evolutionary algorithms. Evolutionary Computation, 21( 4), 659-684.
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      Barros RC, Basgalupp MP, Carvalho ACP de LF de, Freitas AA. Automatic design of decision-tree algorithms with evolutionary algorithms. Evolutionary Computation. 2013 ; 21( 4): 659-684.[citado 2024 out. 02 ]
    • Vancouver

      Barros RC, Basgalupp MP, Carvalho ACP de LF de, Freitas AA. Automatic design of decision-tree algorithms with evolutionary algorithms. Evolutionary Computation. 2013 ; 21( 4): 659-684.[citado 2024 out. 02 ]
  • Source: Journal of Information and Data Management - JIDM. Conference titles: Brazilian Symposium on Databases - SBBD. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      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: 02 out. 2024. , 2013
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      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
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      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 2024 out. 02 ] 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 2024 out. 02 ] Available from: http://seer.lcc.ufmg.br/index.php/jidm/article/view/256
  • Source: Lecture Notes in Artificial Intelligence. Conference titles: European Conference on Machine Learning and Knowledge Discovery in Databases - ECML PKDD. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      BARROS, Rodrigo C et al. Probabilistic clustering for hierarchical multi-label classification of protein functions. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. Disponível em: https://doi.org/10.1007/978-3-642-40991-2_25. Acesso em: 02 out. 2024. , 2013
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      Barros, R. C., Cerri, R., Freitas, A. A., & Carvalho, A. C. P. de L. F. de. (2013). Probabilistic clustering for hierarchical multi-label classification of protein functions. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. doi:10.1007/978-3-642-40991-2_25
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      Barros RC, Cerri R, Freitas AA, Carvalho ACP de LF de. Probabilistic clustering for hierarchical multi-label classification of protein functions [Internet]. Lecture Notes in Artificial Intelligence. 2013 ; 8189 385-400.[citado 2024 out. 02 ] Available from: https://doi.org/10.1007/978-3-642-40991-2_25
    • Vancouver

      Barros RC, Cerri R, Freitas AA, Carvalho ACP de LF de. Probabilistic clustering for hierarchical multi-label classification of protein functions [Internet]. Lecture Notes in Artificial Intelligence. 2013 ; 8189 385-400.[citado 2024 out. 02 ] Available from: https://doi.org/10.1007/978-3-642-40991-2_25
  • Source: Proceedings. Conference titles: IEEE Congress on Evolutionary Computation - CEC. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CERRI, Ricardo et al. A grammatical evolution algorithm for generation of hierarchical multi-label classification rules. 2013, Anais.. Piscataway: IEEE, 2013. Disponível em: https://doi.org/10.1109/CEC.2013.6557604. Acesso em: 02 out. 2024.
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      Cerri, R., Barros, R. C., Carvalho, A. C. P. de L. F. de, & Freitas, A. A. (2013). A grammatical evolution algorithm for generation of hierarchical multi-label classification rules. In Proceedings. Piscataway: IEEE. doi:10.1109/CEC.2013.6557604
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      Cerri R, Barros RC, Carvalho ACP de LF de, Freitas AA. A grammatical evolution algorithm for generation of hierarchical multi-label classification rules [Internet]. Proceedings. 2013 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/CEC.2013.6557604
    • Vancouver

      Cerri R, Barros RC, Carvalho ACP de LF de, Freitas AA. A grammatical evolution algorithm for generation of hierarchical multi-label classification rules [Internet]. Proceedings. 2013 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/CEC.2013.6557604
  • Source: ACM Computing Surveys. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      SILVA, Jonathan A et al. Data stream clustering: a survey. ACM Computing Surveys, v. 46, n. 1, p. 13:1-13:31, 2013Tradução . . Disponível em: https://doi.org/10.1145/2522968.2522981. Acesso em: 02 out. 2024.
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      Silva, J. A., Faria, E. R., Barros, R. C., Hruschka, E. R., Carvalho, A. C. P. de L. F. de, & Gama, J. (2013). Data stream clustering: a survey. ACM Computing Surveys, 46( 1), 13:1-13:31. doi:10.1145/2522968.2522981
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      Silva JA, Faria ER, Barros RC, Hruschka ER, Carvalho ACP de LF de, Gama J. Data stream clustering: a survey [Internet]. ACM Computing Surveys. 2013 ; 46( 1): 13:1-13:31.[citado 2024 out. 02 ] Available from: https://doi.org/10.1145/2522968.2522981
    • Vancouver

      Silva JA, Faria ER, Barros RC, Hruschka ER, Carvalho ACP de LF de, Gama J. Data stream clustering: a survey [Internet]. ACM Computing Surveys. 2013 ; 46( 1): 13:1-13:31.[citado 2024 out. 02 ] Available from: https://doi.org/10.1145/2522968.2522981
  • Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CERRI, Ricardo e BARROS, Rodrigo C e CARVALHO, André Carlos Ponce de Leon Ferreira de. Neural networks for hierarchical classification of G-Protein Coupled Receptors. 2013, Anais.. Los Alamitos: Conference Publishing Services, 2013. Disponível em: https://doi.org/10.1109/BRACIS.2013.29. Acesso em: 02 out. 2024.
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      Cerri, R., Barros, R. C., & Carvalho, A. C. P. de L. F. de. (2013). Neural networks for hierarchical classification of G-Protein Coupled Receptors. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/BRACIS.2013.29
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      Cerri R, Barros RC, Carvalho ACP de LF de. Neural networks for hierarchical classification of G-Protein Coupled Receptors [Internet]. Proceedings. 2013 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/BRACIS.2013.29
    • Vancouver

      Cerri R, Barros RC, Carvalho ACP de LF de. Neural networks for hierarchical classification of G-Protein Coupled Receptors [Internet]. Proceedings. 2013 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/BRACIS.2013.29
  • Source: Poster. Conference titles: Symposium on Applied Computing - SAC. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      FARIA, Elaine R et al. Improving the offline clustering stage of data stream algorithms in scenarios with variable number of clusters. 2012, Anais.. New York: ACM, 2012. . Acesso em: 02 out. 2024.
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      Faria, E. R., Barros, R. C., Carvalho, A. C. P. de L. F. de, & Gama, J. (2012). Improving the offline clustering stage of data stream algorithms in scenarios with variable number of clusters. In Poster. New York: ACM.
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      Faria ER, Barros RC, Carvalho ACP de LF de, Gama J. Improving the offline clustering stage of data stream algorithms in scenarios with variable number of clusters. Poster. 2012 ;[citado 2024 out. 02 ]
    • Vancouver

      Faria ER, Barros RC, Carvalho ACP de LF de, Gama J. Improving the offline clustering stage of data stream algorithms in scenarios with variable number of clusters. Poster. 2012 ;[citado 2024 out. 02 ]
  • Source: Proceedings. Conference titles: Symposium on Applied Computing - SAC. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CERRI, Ricardo e BARROS, Rodrigo C e CARVALHO, André Carlos Ponce de Leon Ferreira de. A genetic algorithm for hierarchical multi-label classification. 2012, Anais.. New York: ACM, 2012. . Acesso em: 02 out. 2024.
    • APA

      Cerri, R., Barros, R. C., & Carvalho, A. C. P. de L. F. de. (2012). A genetic algorithm for hierarchical multi-label classification. In Proceedings. New York: ACM.
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      Cerri R, Barros RC, Carvalho ACP de LF de. A genetic algorithm for hierarchical multi-label classification. Proceedings. 2012 ;[citado 2024 out. 02 ]
    • Vancouver

      Cerri R, Barros RC, Carvalho ACP de LF de. A genetic algorithm for hierarchical multi-label classification. Proceedings. 2012 ;[citado 2024 out. 02 ]
  • Source: BMC Bioinformatics. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

    Acesso à fonteDOIHow to cite
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    • ABNT

      BARROS, Rodrigo C et al. Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data. BMC Bioinformatics, v. no 2012, n. 1, p. 310-1-310-24, 2012Tradução . . Disponível em: https://doi.org/10.1186/1471-2105-13-310. Acesso em: 02 out. 2024.
    • APA

      Barros, R. C., Winck, A. T., Machado, K. S., Basgalupp, M. P., Carvalho, A. C. P. de L. F. de, Ruiz, D. D., & Souza, O. N. de. (2012). Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data. BMC Bioinformatics, no 2012( 1), 310-1-310-24. doi:10.1186/1471-2105-13-310
    • NLM

      Barros RC, Winck AT, Machado KS, Basgalupp MP, Carvalho ACP de LF de, Ruiz DD, Souza ON de. Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data [Internet]. BMC Bioinformatics. 2012 ; no 2012( 1): 310-1-310-24.[citado 2024 out. 02 ] Available from: https://doi.org/10.1186/1471-2105-13-310
    • Vancouver

      Barros RC, Winck AT, Machado KS, Basgalupp MP, Carvalho ACP de LF de, Ruiz DD, Souza ON de. Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data [Internet]. BMC Bioinformatics. 2012 ; no 2012( 1): 310-1-310-24.[citado 2024 out. 02 ] Available from: https://doi.org/10.1186/1471-2105-13-310

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