Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Symposium on Artificial Intelligence : Advances in Artificial Intelligence - SBIA. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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: 06 set. 2024. , 2012APA
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_8NLM
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 2024 set. 06 ] Available from: https://doi.org/10.1007/978-3-642-34459-6_8Vancouver
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 2024 set. 06 ] Available from: https://doi.org/10.1007/978-3-642-34459-6_8