AN EXTENSIBLE ENSEMBLE ENVIRONMENT FOR TIME SERIES FORECASTING

There have been diverse works demonstrating that ensembles can improve the performance over any individual solution for time series forecasting. This work presents an extensible environment that can be used to create, experiment and analyse ensembles for time series forecasting. Usually, the analyst develops the individual solution and the ensemble algorithms for each experiment. The proposed environment intends to provide a flexible tool for the analyst to include, configure and experiment with individual solutions and to build and execute ensembles. In this paper, we describe the environment, its features and we present a simple experiment on its usage.