Filtros : "MONARD, MARIA CAROLINA" "Estados Unidos" Removido: "Electronic Notes in Theoretical Computer Science" Limpar

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  • Source: Information Sciences. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, FUZZY (INTELIGÊNCIA ARTIFICIAL)

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      CINTRA, M. E e CAMARGO, H. A e MONARD, Maria Carolina. Genetic generation of fuzzy systems with rule extraction using formal concept analysis. Information Sciences, v. 349-350, p. 199-215, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2016.02.026. Acesso em: 27 nov. 2025.
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      Cintra, M. E., Camargo, H. A., & Monard, M. C. (2016). Genetic generation of fuzzy systems with rule extraction using formal concept analysis. Information Sciences, 349-350, 199-215. doi:10.1016/j.ins.2016.02.026
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      Cintra ME, Camargo HA, Monard MC. Genetic generation of fuzzy systems with rule extraction using formal concept analysis [Internet]. Information Sciences. 2016 ; 349-350 199-215.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.ins.2016.02.026
    • Vancouver

      Cintra ME, Camargo HA, Monard MC. Genetic generation of fuzzy systems with rule extraction using formal concept analysis [Internet]. Information Sciences. 2016 ; 349-350 199-215.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.ins.2016.02.026
  • Source: Proceedings. Conference titles: International Joint Conference on Artificial Intelligence - IJCAI. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL

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      BRAGA, Igor. Stochastic density ratio estimation and its application to feature selection. 2015, Anais.. Palo Alto: AAAI Press, 2015. Disponível em: http://ijcai.org/papers15/Papers/IJCAI15-620.pdf. Acesso em: 27 nov. 2025.
    • APA

      Braga, I. (2015). Stochastic density ratio estimation and its application to feature selection. In Proceedings. Palo Alto: AAAI Press. Recuperado de http://ijcai.org/papers15/Papers/IJCAI15-620.pdf
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      Braga I. Stochastic density ratio estimation and its application to feature selection [Internet]. Proceedings. 2015 ;[citado 2025 nov. 27 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-620.pdf
    • Vancouver

      Braga I. Stochastic density ratio estimation and its application to feature selection [Internet]. Proceedings. 2015 ;[citado 2025 nov. 27 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-620.pdf
  • Source: Proceedings. Conference titles: IEEE International Conference on Fuzzy Systems - FUZZ-IEEE. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, FUZZY (INTELIGÊNCIA ARTIFICIAL)

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      CINTRA, Marcos E e MONARD, Maria Carolina e CAMARGO, Heloisa A. FCA-Based Rule Generator: a framework for the genetic generation of fuzzy classification systems using formal concept analysis. 2015, Anais.. Piscataway: IEEE, 2015. Disponível em: https://doi.org/10.1109/FUZZ-IEEE.2015.7337950. Acesso em: 27 nov. 2025.
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      Cintra, M. E., Monard, M. C., & Camargo, H. A. (2015). FCA-Based Rule Generator: a framework for the genetic generation of fuzzy classification systems using formal concept analysis. In Proceedings. Piscataway: IEEE. doi:10.1109/FUZZ-IEEE.2015.7337950
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      Cintra ME, Monard MC, Camargo HA. FCA-Based Rule Generator: a framework for the genetic generation of fuzzy classification systems using formal concept analysis [Internet]. Proceedings. 2015 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/FUZZ-IEEE.2015.7337950
    • Vancouver

      Cintra ME, Monard MC, Camargo HA. FCA-Based Rule Generator: a framework for the genetic generation of fuzzy classification systems using formal concept analysis [Internet]. Proceedings. 2015 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/FUZZ-IEEE.2015.7337950
  • Source: Proceedings. Conference titles: International Joint Conference on Artificial Intelligence - IJCAI. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL

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      SPOLAÔR, Newton e MONARD, Maria Carolina e LEE, Huei Diana. Feature selection for multi-label learning. 2015, Anais.. Palo Alto: AAAI Press, 2015. Disponível em: http://ijcai.org/papers15/Papers/IJCAI15-648.pdf. Acesso em: 27 nov. 2025.
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      Spolaôr, N., Monard, M. C., & Lee, H. D. (2015). Feature selection for multi-label learning. In Proceedings. Palo Alto: AAAI Press. Recuperado de http://ijcai.org/papers15/Papers/IJCAI15-648.pdf
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      Spolaôr N, Monard MC, Lee HD. Feature selection for multi-label learning [Internet]. Proceedings. 2015 ;[citado 2025 nov. 27 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-648.pdf
    • Vancouver

      Spolaôr N, Monard MC, Lee HD. Feature selection for multi-label learning [Internet]. Proceedings. 2015 ;[citado 2025 nov. 27 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-648.pdf
  • Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL

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      SPOLAÔR, Newton et al. Label construction for multi-label feature selection. 2014, Anais.. Los Alamitos: Conference Publishing Services, 2014. Disponível em: https://doi.org/10.1109/BRACIS.2014.52. Acesso em: 27 nov. 2025.
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      Spolaôr, N., Monard, M. C., Tsoumakas, G., & Lee, H. D. (2014). Label construction for multi-label feature selection. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/BRACIS.2014.52
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      Spolaôr N, Monard MC, Tsoumakas G, Lee HD. Label construction for multi-label feature selection [Internet]. Proceedings. 2014 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2014.52
    • Vancouver

      Spolaôr N, Monard MC, Tsoumakas G, Lee HD. Label construction for multi-label feature selection [Internet]. Proceedings. 2014 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2014.52
  • Source: Proceedings. Conference titles: Latin American Computing Conference - CLEI. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, COMPUTAÇÃO GRÁFICA

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      CARVALHO, Victor Augusto Moraes et al. A framework for multi-label exploratory data analysis: ML-EDA. 2014, Anais.. Red Hook: IEEE, 2014. Disponível em: https://doi.org/10.1109/CLEI.2014.6965166. Acesso em: 27 nov. 2025.
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      Carvalho, V. A. M., Spolaôr, N., Cherman, E. A., & Monard, M. C. (2014). A framework for multi-label exploratory data analysis: ML-EDA. In Proceedings. Red Hook: IEEE. doi:10.1109/CLEI.2014.6965166
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      Carvalho VAM, Spolaôr N, Cherman EA, Monard MC. A framework for multi-label exploratory data analysis: ML-EDA [Internet]. Proceedings. 2014 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/CLEI.2014.6965166
    • Vancouver

      Carvalho VAM, Spolaôr N, Cherman EA, Monard MC. A framework for multi-label exploratory data analysis: ML-EDA [Internet]. Proceedings. 2014 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/CLEI.2014.6965166
  • Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      SPOLAÔR, Newton et al. ReliefF for multi-label feature selection. 2013, Anais.. Los Alamitos: Conference Publishing Services, 2013. Disponível em: https://doi.org/10.1109/BRACIS.2013.10. Acesso em: 27 nov. 2025.
    • APA

      Spolaôr, N., Cherman, E. A., Monard, M. C., & Lee, H. D. (2013). ReliefF for multi-label feature selection. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/BRACIS.2013.10
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      Spolaôr N, Cherman EA, Monard MC, Lee HD. ReliefF for multi-label feature selection [Internet]. Proceedings. 2013 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2013.10
    • Vancouver

      Spolaôr N, Cherman EA, Monard MC, Lee HD. ReliefF for multi-label feature selection [Internet]. Proceedings. 2013 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2013.10
  • Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      BRAGA, Igor e MONARD, Maria Carolina. Statistical and heuristic model selection in regularized least-squares. 2013, Anais.. Los Alamitos: Conference Publishing Services, 2013. Disponível em: https://doi.org/10.1109/BRACIS.2013.46. Acesso em: 27 nov. 2025.
    • APA

      Braga, I., & Monard, M. C. (2013). Statistical and heuristic model selection in regularized least-squares. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/BRACIS.2013.46
    • NLM

      Braga I, Monard MC. Statistical and heuristic model selection in regularized least-squares [Internet]. Proceedings. 2013 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2013.46
    • Vancouver

      Braga I, Monard MC. Statistical and heuristic model selection in regularized least-squares [Internet]. Proceedings. 2013 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2013.46
  • Source: Proceedings. Conference titles: IEEE World Congress on Computational Intelligence - WCCI. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CINTRA, Marcos E e MONARD, Maria Carolina e CAMARGO, Heloisa A. Using fuzzy formal concepts in the genetic generation of fuzzy systems. 2012, Anais.. Piscataway: IEEE, 2012. Disponível em: https://doi.org/10.1109/FUZZ-IEEE.2012.6251310. Acesso em: 27 nov. 2025.
    • APA

      Cintra, M. E., Monard, M. C., & Camargo, H. A. (2012). Using fuzzy formal concepts in the genetic generation of fuzzy systems. In Proceedings. Piscataway: IEEE. doi:10.1109/FUZZ-IEEE.2012.6251310
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      Cintra ME, Monard MC, Camargo HA. Using fuzzy formal concepts in the genetic generation of fuzzy systems [Internet]. Proceedings. 2012 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/FUZZ-IEEE.2012.6251310
    • Vancouver

      Cintra ME, Monard MC, Camargo HA. Using fuzzy formal concepts in the genetic generation of fuzzy systems [Internet]. Proceedings. 2012 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/FUZZ-IEEE.2012.6251310
  • Source: Proceedings. Conference titles: International Conference on Intelligent Systems Design and Applications - ISDA. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CINTRA, Marcos E et al. The use of fuzzy decision trees for coffee rust warning in Brazilian crops. 2011, Anais.. Piscataway: IEEE, 2011. Disponível em: https://doi.org/10.1109/ISDA.2011.6121847. Acesso em: 27 nov. 2025.
    • APA

      Cintra, M. E., Meira, C. A. A., Monard, M. C., Camargo, H. A., & Rodrigues, L. H. A. (2011). The use of fuzzy decision trees for coffee rust warning in Brazilian crops. In Proceedings. Piscataway: IEEE. doi:10.1109/ISDA.2011.6121847
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      Cintra ME, Meira CAA, Monard MC, Camargo HA, Rodrigues LHA. The use of fuzzy decision trees for coffee rust warning in Brazilian crops [Internet]. Proceedings. 2011 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/ISDA.2011.6121847
    • Vancouver

      Cintra ME, Meira CAA, Monard MC, Camargo HA, Rodrigues LHA. The use of fuzzy decision trees for coffee rust warning in Brazilian crops [Internet]. Proceedings. 2011 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/ISDA.2011.6121847
  • Source: Proceedings. Conference titles: World Conference on Soft Computing - WConSC. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CINTRA, Marcos Evandro e MONARD, Maria Carolina e CAMARGO, Heloisa de Arruda. Fuzzy and classic rule learning methods: a comparative analysis. 2011, Anais.. San Francisco: San Francisco State University, 2011. . Acesso em: 27 nov. 2025.
    • APA

      Cintra, M. E., Monard, M. C., & Camargo, H. de A. (2011). Fuzzy and classic rule learning methods: a comparative analysis. In Proceedings. San Francisco: San Francisco State University.
    • NLM

      Cintra ME, Monard MC, Camargo H de A. Fuzzy and classic rule learning methods: a comparative analysis. Proceedings. 2011 ;[citado 2025 nov. 27 ]
    • Vancouver

      Cintra ME, Monard MC, Camargo H de A. Fuzzy and classic rule learning methods: a comparative analysis. Proceedings. 2011 ;[citado 2025 nov. 27 ]
  • Source: IEEE Transactions on Knowledge and Data Engineering. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      PRATI, Ronaldo Cristiano e BATISTA, Gustavo Enrique de Almeida Prado Alves e MONARD, Maria Carolina. A survey on graphical methods for classification predictive performance evaluation. IEEE Transactions on Knowledge and Data Engineering, v. 23, n. 11, p. 1601-1618, 2011Tradução . . Disponível em: https://doi.org/10.1109/TKDE.2011.59. Acesso em: 27 nov. 2025.
    • APA

      Prati, R. C., Batista, G. E. de A. P. A., & Monard, M. C. (2011). A survey on graphical methods for classification predictive performance evaluation. IEEE Transactions on Knowledge and Data Engineering, 23( 11), 1601-1618. doi:10.1109/TKDE.2011.59
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      Prati RC, Batista GE de APA, Monard MC. A survey on graphical methods for classification predictive performance evaluation [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2011 ; 23( 11): 1601-1618.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/TKDE.2011.59
    • Vancouver

      Prati RC, Batista GE de APA, Monard MC. A survey on graphical methods for classification predictive performance evaluation [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2011 ; 23( 11): 1601-1618.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/TKDE.2011.59
  • Source: Proceedings. Conference titles: International Conference on Hybrid Intelligent Systems - HIS. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CINTRA, Marcos E et al. On the estimation of the number of fuzzy sets for fuzzy rule-based classification systems. 2011, Anais.. Piscataway: IEEE, 2011. Disponível em: https://doi.org/10.1109/HIS.2011.6122107. Acesso em: 27 nov. 2025.
    • APA

      Cintra, M. E., Monard, M. C., Cherman, E. A., & Camargo, H. de A. (2011). On the estimation of the number of fuzzy sets for fuzzy rule-based classification systems. In Proceedings. Piscataway: IEEE. doi:10.1109/HIS.2011.6122107
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      Cintra ME, Monard MC, Cherman EA, Camargo H de A. On the estimation of the number of fuzzy sets for fuzzy rule-based classification systems [Internet]. Proceedings. 2011 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/HIS.2011.6122107
    • Vancouver

      Cintra ME, Monard MC, Cherman EA, Camargo H de A. On the estimation of the number of fuzzy sets for fuzzy rule-based classification systems [Internet]. Proceedings. 2011 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/HIS.2011.6122107
  • Source: Proceedings. Conference titles: Joint Conference. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CINTRA, Marcos Evandro e MONARD, Maria Carolina e CAMARGO, Heloisa de Arruda. An evaluation of rule-based classification models induced by a fuzzy method and two classic learning algorithms. 2010, Anais.. Los Alamitos: IEEE Computer Society, 2010. Disponível em: https://doi.org/10.1109/SBRN.2010.40. Acesso em: 27 nov. 2025.
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      Cintra, M. E., Monard, M. C., & Camargo, H. de A. (2010). An evaluation of rule-based classification models induced by a fuzzy method and two classic learning algorithms. In Proceedings. Los Alamitos: IEEE Computer Society. doi:10.1109/SBRN.2010.40
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      Cintra ME, Monard MC, Camargo H de A. An evaluation of rule-based classification models induced by a fuzzy method and two classic learning algorithms [Internet]. Proceedings. 2010 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/SBRN.2010.40
    • Vancouver

      Cintra ME, Monard MC, Camargo H de A. An evaluation of rule-based classification models induced by a fuzzy method and two classic learning algorithms [Internet]. Proceedings. 2010 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/SBRN.2010.40
  • Source: Proceedings. Conference titles: Indian International Conference on Artificial Intelligence - IICAI. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      PRATI, Ronaldo Cristiano e BATISTA, Gustavo Enrique de Almeida Prado Alves e MONARD, Maria Carolina. Data mining with imbalanced class distributions: concepts and methods. 2009, Anais.. Tallahassee: IICAI, 2009. . Acesso em: 27 nov. 2025.
    • APA

      Prati, R. C., Batista, G. E. de A. P. A., & Monard, M. C. (2009). Data mining with imbalanced class distributions: concepts and methods. In Proceedings. Tallahassee: IICAI.
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      Prati RC, Batista GE de APA, Monard MC. Data mining with imbalanced class distributions: concepts and methods. Proceedings. 2009 ;[citado 2025 nov. 27 ]
    • Vancouver

      Prati RC, Batista GE de APA, Monard MC. Data mining with imbalanced class distributions: concepts and methods. Proceedings. 2009 ;[citado 2025 nov. 27 ]
  • Source: IEEE Latin America Transactions. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      SOARES, Matheus Victor Brum e PRATI, Ronaldo Cristiano e MONARD, Maria Carolina. Improvements on the Porter's stemming algorithm for portuguese. IEEE Latin America Transactions, v. 7, n. 4, p. 472-477, 2009Tradução . . Disponível em: http://ewh.ieee.org/reg/9/etrans/por/publicacoes.php. Acesso em: 27 nov. 2025.
    • APA

      Soares, M. V. B., Prati, R. C., & Monard, M. C. (2009). Improvements on the Porter's stemming algorithm for portuguese. IEEE Latin America Transactions, 7( 4), 472-477. Recuperado de http://ewh.ieee.org/reg/9/etrans/por/publicacoes.php
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      Soares MVB, Prati RC, Monard MC. Improvements on the Porter's stemming algorithm for portuguese [Internet]. IEEE Latin America Transactions. 2009 ; 7( 4): 472-477.[citado 2025 nov. 27 ] Available from: http://ewh.ieee.org/reg/9/etrans/por/publicacoes.php
    • Vancouver

      Soares MVB, Prati RC, Monard MC. Improvements on the Porter's stemming algorithm for portuguese [Internet]. IEEE Latin America Transactions. 2009 ; 7( 4): 472-477.[citado 2025 nov. 27 ] Available from: http://ewh.ieee.org/reg/9/etrans/por/publicacoes.php
  • Source: IEEE Latin America Transactions. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      PRATI, Ronaldo Cristiano e BATISTA, Gustavo Enrique de Almeida Prado Alves e MONARD, Maria Carolina. Curvas ROC para avaliação de classificadores. IEEE Latin America Transactions, v. 6, n. 2, p. 215-222, 2008Tradução . . Disponível em: http://ieeexplore.ieee.org/stamp/stamp.do?arnumber=4609920&isnumber=4609907. Acesso em: 27 nov. 2025.
    • APA

      Prati, R. C., Batista, G. E. de A. P. A., & Monard, M. C. (2008). Curvas ROC para avaliação de classificadores. IEEE Latin America Transactions, 6( 2), 215-222. Recuperado de http://ieeexplore.ieee.org/stamp/stamp.do?arnumber=4609920&isnumber=4609907
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      Prati RC, Batista GE de APA, Monard MC. Curvas ROC para avaliação de classificadores [Internet]. IEEE Latin America Transactions. 2008 ; 6( 2): 215-222.[citado 2025 nov. 27 ] Available from: http://ieeexplore.ieee.org/stamp/stamp.do?arnumber=4609920&isnumber=4609907
    • Vancouver

      Prati RC, Batista GE de APA, Monard MC. Curvas ROC para avaliação de classificadores [Internet]. IEEE Latin America Transactions. 2008 ; 6( 2): 215-222.[citado 2025 nov. 27 ] Available from: http://ieeexplore.ieee.org/stamp/stamp.do?arnumber=4609920&isnumber=4609907
  • Source: Artificial Intelligence and Practice II, v. 276. Conference titles: IFIP World Computer Congress. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      PRATI, Ronaldo Cristiano e BATISTA, Gustavo Enrique de Almeida Prado Alves e MONARD, Maria Carolina. A study with class imbalance and random sampling for a decision tree learning system. Artificial Intelligence and Practice II, v. 276. Boston: Springer. . Acesso em: 27 nov. 2025. , 2008
    • APA

      Prati, R. C., Batista, G. E. de A. P. A., & Monard, M. C. (2008). A study with class imbalance and random sampling for a decision tree learning system. Artificial Intelligence and Practice II, v. 276. Boston: Springer.
    • NLM

      Prati RC, Batista GE de APA, Monard MC. A study with class imbalance and random sampling for a decision tree learning system. Artificial Intelligence and Practice II, v. 276. 2008 ;[citado 2025 nov. 27 ]
    • Vancouver

      Prati RC, Batista GE de APA, Monard MC. A study with class imbalance and random sampling for a decision tree learning system. Artificial Intelligence and Practice II, v. 276. 2008 ;[citado 2025 nov. 27 ]
  • Source: Emerging technologies of text mining : techniques and applications. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      MATSUBARA, Edson Takashi e MONARD, Maria Carolina e PRATI, Ronaldo Cristiano. Exploring unclassified texts using multiview semisupervised learning. Emerging technologies of text mining : techniques and applications. Tradução . New York: Information Science Reference, 2007. . . Acesso em: 27 nov. 2025.
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      Matsubara, E. T., Monard, M. C., & Prati, R. C. (2007). Exploring unclassified texts using multiview semisupervised learning. In Emerging technologies of text mining : techniques and applications. New York: Information Science Reference.
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      Matsubara ET, Monard MC, Prati RC. Exploring unclassified texts using multiview semisupervised learning. In: Emerging technologies of text mining : techniques and applications. New York: Information Science Reference; 2007. [citado 2025 nov. 27 ]
    • Vancouver

      Matsubara ET, Monard MC, Prati RC. Exploring unclassified texts using multiview semisupervised learning. In: Emerging technologies of text mining : techniques and applications. New York: Information Science Reference; 2007. [citado 2025 nov. 27 ]
  • Source: Proceedings. Conference titles: International Conference on Hybrid Intelligent Systems. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      BERNARDINI, Flávia Cristina e MONARD, Maria Carolina e PRATI, Ronaldo Cristiano. Constructing ensembles of symbolic classifiers. 2005, Anais.. Los Alamitos: IEEE Computer Society, 2005. . Acesso em: 27 nov. 2025.
    • APA

      Bernardini, F. C., Monard, M. C., & Prati, R. C. (2005). Constructing ensembles of symbolic classifiers. In Proceedings. Los Alamitos: IEEE Computer Society.
    • NLM

      Bernardini FC, Monard MC, Prati RC. Constructing ensembles of symbolic classifiers. Proceedings. 2005 ;[citado 2025 nov. 27 ]
    • Vancouver

      Bernardini FC, Monard MC, Prati RC. Constructing ensembles of symbolic classifiers. Proceedings. 2005 ;[citado 2025 nov. 27 ]

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