  This paper analyzes comparatively the performance of Random Forests and
Gradient Boosting algorithms in the field of forecasting the energy consumption
based on historical data. The two algorithms are applied in order to forecast
the energy consumption individually, and then combined together by using a
Weighted Average Ensemble Method. The comparison among the achieved
experimental results proves that the Weighted Average Ensemble Method provides
more accurate results than each of the two algorithms applied alone.
