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Double quantization of the regressor space for long-term time series prediction: method and proof of stability
Geoffroy Simon1, Amaury Lendasse, Marie Cottrell
1Machine Learning Group (DICE), Université Catholique de Louvain, Place du Levant 3, B-1348 Louvain-la-Neuve, Belgium. simon@dice.ucl.ac.be
Abstract:
The Kohonen self-organization map is usually considered as a classification or clustering tool, with only a few applications in time series prediction. In this paper, a particular time series forecasting method based on Kohonen maps is described. This method has been specifically designed for the prediction of long-term trends. The proof of the stability of the method for long-term forecasting is given, as well as illustrations of the utilization of the method both in the scalar and vectorial cases.
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