arXivEconometrics & Forecasting

Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series

The paper outlines a successful method for point and probabilistic forecasting using a mix of machine learning models, as demonstrated in the M5 Competition, highlighting the significance of diverse models and careful validation example selection.