Prediction of secondary testosterone deficiency using machine learning: A comparative analysis of ensemble and base classifiers, probability calibration, and sampling strategies in a slightly imbalanced dataset
Titel:
Prediction of secondary testosterone deficiency using machine learning: A comparative analysis of ensemble and base classifiers, probability calibration, and sampling strategies in a slightly imbalanced dataset
Auteur:
Novaes, Monique Tonani Ferreira de Carvalho, Osmar Luiz Guimarães Ferreira, Pedro Henrique Nunes Tiraboschi, Taciana Leonel Silva, Caroline Santos Zambrano, Jean Carlos Gomes, Cristiano Mendes de Paula Miranda, Eduardo Abílio de Carvalho Júnior, Osmar de Bessa Júnior, José