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Filtros : "MONARD, MARIA CAROLINA" "Lecture Notes in Artifical Intelligence" Removido: "Congress of Logic Aplied to Technology" Limpar

Filtros

Trabalho de evento-anais periodico
Evaluating ReliefF-based multi-label feature selection algorithm (2014)
Spolaôr, Newton; Monard, Maria Carolina
Source: Lecture Notes in Artifical Intelligence. Conference titles: Ibero-American Conference on Artificial Intelligence - IBERAMIA : Advances in Artificial Intelligence. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SPOLAÔR, Newton e MONARD, Maria Carolina. Evaluating ReliefF-based multi-label feature selection algorithm. Lecture Notes in Artifical Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-12027-0_16. Acesso em: 28 nov. 2025. , 2014
APA
Spolaôr, N., & Monard, M. C. (2014). Evaluating ReliefF-based multi-label feature selection algorithm. Lecture Notes in Artifical Intelligence. Cham: Springer. doi:10.1007/978-3-319-12027-0_16
NLM
Spolaôr N, Monard MC. Evaluating ReliefF-based multi-label feature selection algorithm [Internet]. Lecture Notes in Artifical Intelligence. 2014 ; 8864 194-205.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/978-3-319-12027-0_16
Vancouver
Spolaôr N, Monard MC. Evaluating ReliefF-based multi-label feature selection algorithm [Internet]. Lecture Notes in Artifical Intelligence. 2014 ; 8864 194-205.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/978-3-319-12027-0_16
Trabalho de evento-anais periodico
On the estimation of predictive evaluation measure baselines for multi-label learning (2012)
Metz, Jean; Abreu, Luís F. D. de; Cherman, Everton A; Monard, Maria Carolina
Source: Lecture Notes in Artifical Intelligence. Conference titles: Ibero-American Conference on Artificial Intelligence - IBERAMIA : Advances in Artificial Intelligence. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
METZ, Jean et al. On the estimation of predictive evaluation measure baselines for multi-label learning. Lecture Notes in Artifical Intelligence. Berlin: Springer-Verlag. Disponível em: https://doi.org/10.1007/978-3-642-34654-5_20. Acesso em: 28 nov. 2025. , 2012
APA
Metz, J., Abreu, L. F. D. de, Cherman, E. A., & Monard, M. C. (2012). On the estimation of predictive evaluation measure baselines for multi-label learning. Lecture Notes in Artifical Intelligence. Berlin: Springer-Verlag. doi:10.1007/978-3-642-34654-5_20
NLM
Metz J, Abreu LFD de, Cherman EA, Monard MC. On the estimation of predictive evaluation measure baselines for multi-label learning [Internet]. Lecture Notes in Artifical Intelligence. 2012 ; 7637 189-198.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/978-3-642-34654-5_20
Vancouver
Metz J, Abreu LFD de, Cherman EA, Monard MC. On the estimation of predictive evaluation measure baselines for multi-label learning [Internet]. Lecture Notes in Artifical Intelligence. 2012 ; 7637 189-198.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/978-3-642-34654-5_20

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