Dynamic Pooling for the Combination of Forecasts generated using Multi Level Learning

— In this paper we provide experimental results and extensions to our previous theoretical findings concerning the combination of forecasts that have been diversified by three different methods: with parameters learned at different data aggregation levels, by thick modeling and by the use of different forecasting methods. An approach of error variance based pooling as proposed by Aiolfi and Timmermann has been compared with flat combinations as well as an alternative pooling approach in which we consider information about the used diversification. An advantage of our approach is that it leads to the generation of novel multi step multi level forecast generation structures that carry out the combination in different steps of pooling corresponding to the different types of diversification. We describe different evolutionary approaches in order to evolve the order of pooling of the diversification dimensions. Extensions of such evolutions allow the generation of more flexible mu...

• Type: Conference
• Year: 2007
• Where: IJCNN
• Authors: Silvia Riedel, Bogdan Gabrys
• Keywords: Alternative Pooling Approach, Combination Structures, IJCNN 2007, Multi Step Combination