Geographic context-based stacking learning for election prediction from socio-economic data (2022)
Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, COMPORTAMENTO ELEITORAL
ABNT
SILVA, Tiago Pinho da e PARMEZAN, Antonio Rafael Sabino e BATISTA, Gustavo Enrique de Almeida Prado Alves. Geographic context-based stacking learning for election prediction from socio-economic data. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_44. Acesso em: 02 nov. 2024. , 2022APA
Silva, T. P. da, Parmezan, A. R. S., & Batista, G. E. de A. P. A. (2022). Geographic context-based stacking learning for election prediction from socio-economic data. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-21686-2_44NLM
Silva TP da, Parmezan ARS, Batista GE de APA. Geographic context-based stacking learning for election prediction from socio-economic data [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 641-657.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_44Vancouver
Silva TP da, Parmezan ARS, Batista GE de APA. Geographic context-based stacking learning for election prediction from socio-economic data [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 641-657.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_44