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

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Vasileios C. Pezoulas, Fanis G. Kalatzis, Themis P. Exarchos, Andreas Goules, Athanasios G. Tzioufas, Dimitrios I. Fotiadis. FHBF: Federated hybrid boosted forests with dropout rates for supervised learning tasks across highly imbalanced clinical datasets. Patterns, 5(1):100893, January 2024. [doi]

Abstract is missing.

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