78 citations · 84 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 78 cited
Implementing local-explainability in Gradient Boosting Trees: Feature Contribution
Ángel Delgado-Panadero, Beatriz Hernández-Lorca, María Teresa García-Ordás +1
Gradient Boost Decision Trees (GBDT) is a powerful additive model based on tree ensembles. Its nature makes GBDT a black-box model even though there are multiple explainable artifi…
cs.LG2024★ 6 cited
A generalized decision tree ensemble based on the NeuralNetworks architecture: Distributed Gradient Boosting Forest (DGBF)
Ángel Delgado-Panadero, José Alberto Benítez-Andrades, María Teresa García-Ordás
Tree ensemble algorithms as RandomForest and GradientBoosting are currently the dominant methods for modeling discrete or tabular data, however, they are unable to perform a hierar…