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Bayesian hierarchical stacking—All models are wrong, but some are somewhere useful
Bayesian hierarchical stacking—All models are wrong, but some are somewhere useful Stacking is a widely used model averaging technique. Like many other ensemble methods, stacking is more effective when model predictive performance is heterogeneous in inputs, in which case we can further improve the stacked mixture with a hierarchical model. In this talk I will focus on the recent development of Bayesian…