Item response theory in sample reweighting to build fairer classifiers (2024)
Source: Communications in Computer and Information Science. Conference titles: Annual International Conference on Information Management and Big Data - SIMBig. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS PARA PROCESSAMENTO, TEORIA DE RESPOSTA AO ITEM
ABNT
MINATEL, Diego et al. Item response theory in sample reweighting to build fairer classifiers. Communications in Computer and Information Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-63616-5_14. Acesso em: 12 dez. 2024. , 2024APA
Minatel, D., Santos, N. R. dos, Silva, V. F. da, Curi, M., & Lopes, A. de A. (2024). Item response theory in sample reweighting to build fairer classifiers. Communications in Computer and Information Science. Cham: Springer. doi:10.1007/978-3-031-63616-5_14NLM
Minatel D, Santos NR dos, Silva VF da, Curi M, Lopes A de A. Item response theory in sample reweighting to build fairer classifiers [Internet]. Communications in Computer and Information Science. 2024 ; 2142 184-198.[citado 2024 dez. 12 ] Available from: https://doi.org/10.1007/978-3-031-63616-5_14Vancouver
Minatel D, Santos NR dos, Silva VF da, Curi M, Lopes A de A. Item response theory in sample reweighting to build fairer classifiers [Internet]. Communications in Computer and Information Science. 2024 ; 2142 184-198.[citado 2024 dez. 12 ] Available from: https://doi.org/10.1007/978-3-031-63616-5_14