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stat.ME2024
A Balanced Statistical Boosting Approach for GAMLSS via New Step Lengths
Alexandra Daub, Andreas Mayr, Boyao Zhang +1
Component-wise gradient boosting algorithms are popular for their intrinsic variable selection and implicit regularization, which can be especially beneficial for very flexible mod…
stat.ME2021
Adaptive Step-Length Selection in Gradient Boosting for Generalized Additive Models for Location, Scale and Shape
Boyao Zhang, Tobias Hepp, Sonja Greven +1
Tuning of model-based boosting algorithms relies mainly on the number of iterations, while the step-length is fixed at a predefined value. For complex models with several predictor…