FHBF: Federated hybrid boosted forests with dropout rates for supervised learning tasks across highly imbalanced clinical datasets

Autor: Pezoulas, Vasileios C., Kalatzis, Fanis, Exarchos, Themis P., Goules, Andreas, Tzioufas, Athanasios G., Fotiadis, Dimitrios I.
Zdroj: In Patterns 12 January 2024 5(1)
Databáze: ScienceDirect