International Journal of Forecasting, to appear. Souhaib Ben Taieb (1) and Rob J Hyndman (2) (1) Machine Learning Group, Department of Computer Science, Université Libre de Bruxelles (2) Department of Econometrics & Business Statistics, Monash University, Clayton, Victoria, Australia Abstract : We describe and analyse the approach used by Team TinTin (Souhaib Ben Taieb and Rob J Hyndman) in the Load Forecasting track of the Kaggle Global Energy Forecasting Competition 2012. The competition involved a hierarchical load forecasting problem for a US utility with 20 geographical zones. The available data consisted of the hourly loads for the 20 zones and hourly temperatures from 11 weather stations, for four and a half
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Rob J Hyndman is