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Trabalho de evento-anais periodico
A note on parameter selection for support vector machines (2013)
Braga, Igor; Carmo, Laís P. do; Benatti, Caio César; Monard, Maria Carolina
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Mexican International Conference on Artificial Intelligence : Advances in Soft Computing and its Applications - MICAI. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BRAGA, Igor et al. A note on parameter selection for support vector machines. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. Disponível em: https://doi.org/10.1007/978-3-642-45111-9_21. Acesso em: 27 nov. 2025. , 2013
APA
Braga, I., Carmo, L. P. do, Benatti, C. C., & Monard, M. C. (2013). A note on parameter selection for support vector machines. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. doi:10.1007/978-3-642-45111-9_21
NLM
Braga I, Carmo LP do, Benatti CC, Monard MC. A note on parameter selection for support vector machines [Internet]. Lecture Notes in Artificial Intelligence. 2013 ; 8266 233-244.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-642-45111-9_21
Vancouver
Braga I, Carmo LP do, Benatti CC, Monard MC. A note on parameter selection for support vector machines [Internet]. Lecture Notes in Artificial Intelligence. 2013 ; 8266 233-244.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-642-45111-9_21
Trabalho de evento-anais periodico
Filter approach feature selection methods to support multi-label learning based on ReliefF and information gain (2012)
Spolaôr, Newton; Cherman, Everton Alvares; Monard, Maria Carolina ; Lee, Huei Diana
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Symposium on Artificial Intelligence : Advances in Artificial Intelligence - SBIA. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SPOLAÔR, Newton et al. Filter approach feature selection methods to support multi-label learning based on ReliefF and information gain. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. Disponível em: https://doi.org/10.1007/978-3-642-34459-6_8. Acesso em: 27 nov. 2025. , 2012
APA
Spolaôr, N., Cherman, E. A., Monard, M. C., & Lee, H. D. (2012). Filter approach feature selection methods to support multi-label learning based on ReliefF and information gain. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. doi:10.1007/978-3-642-34459-6_8
NLM
Spolaôr N, Cherman EA, Monard MC, Lee HD. Filter approach feature selection methods to support multi-label learning based on ReliefF and information gain [Internet]. Lecture Notes in Artificial Intelligence. 2012 ; 7589 72-81.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-642-34459-6_8
Vancouver
Spolaôr N, Cherman EA, Monard MC, Lee HD. Filter approach feature selection methods to support multi-label learning based on ReliefF and information gain [Internet]. Lecture Notes in Artificial Intelligence. 2012 ; 7589 72-81.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-642-34459-6_8
Trabalho de evento-anais periodico
Class imbalances versus class overlapping:: an analysis of a learning (2004)
Prati, Ronaldo Cristiano; Batista, Gustavo Enrique de Almeida Prado Alves; Monard, Maria Carolina
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Mexican International Conference on Artificial Intelligence. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PRATI, Ronaldo Cristiano e BATISTA, Gustavo Enrique de Almeida Prado Alves e MONARD, Maria Carolina. Class imbalances versus class overlapping:: an analysis of a learning. Lecture Notes in Artificial Intelligence. Heidelberger: Springer. . Acesso em: 27 nov. 2025. , 2004
APA
Prati, R. C., Batista, G. E. de A. P. A., & Monard, M. C. (2004). Class imbalances versus class overlapping:: an analysis of a learning. Lecture Notes in Artificial Intelligence. Heidelberger: Springer.
NLM
Prati RC, Batista GE de APA, Monard MC. Class imbalances versus class overlapping:: an analysis of a learning. Lecture Notes in Artificial Intelligence. 2004 ; 2972 312-321.[citado 2025 nov. 27 ]
Vancouver
Prati RC, Batista GE de APA, Monard MC. Class imbalances versus class overlapping:: an analysis of a learning. Lecture Notes in Artificial Intelligence. 2004 ; 2972 312-321.[citado 2025 nov. 27 ]
Trabalho de evento-anais periodico
Improving rule induction precision dor automated annotation by balancing skewed data sets (2004)
Batista, Gustavo Enrique de Almeida Prado Alves; Monard, Maria Carolina ; Bazzan, Ana Lúcia Cetertich
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: International Symposium on Knowledge Exploration in Life Science Informatics. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BATISTA, Gustavo Enrique de Almeida Prado Alves e MONARD, Maria Carolina e BAZZAN, Ana Lúcia Cetertich. Improving rule induction precision dor automated annotation by balancing skewed data sets. Lecture Notes in Artificial Intelligence. Heidelberger: Springer. . Acesso em: 27 nov. 2025. , 2004
APA
Batista, G. E. de A. P. A., Monard, M. C., & Bazzan, A. L. C. (2004). Improving rule induction precision dor automated annotation by balancing skewed data sets. Lecture Notes in Artificial Intelligence. Heidelberger: Springer.
NLM
Batista GE de APA, Monard MC, Bazzan ALC. Improving rule induction precision dor automated annotation by balancing skewed data sets. Lecture Notes in Artificial Intelligence. 2004 ; 3303 20-32.[citado 2025 nov. 27 ]
Vancouver
Batista GE de APA, Monard MC, Bazzan ALC. Improving rule induction precision dor automated annotation by balancing skewed data sets. Lecture Notes in Artificial Intelligence. 2004 ; 3303 20-32.[citado 2025 nov. 27 ]

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