PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Direct and recursive prediction of time series using Mutual information selection
Yongnan Ji, Jin Hao, Nima Reyhani and Amaury Lendasse
In: Computational Intelligence and Bioinspired Systems: 8th International Workshop on Artificial Neural Networks, IWANN 2005, Vilanova i la Geltrú, Barcelona, Spain, June 8-10, 2005. Proceedings Lecture Notes in Computer Science , 3512 (XXV). (2005) Springer-Verlag GmbH , Germany , pp. 1010-1017. ISBN 3-540-26208-3

Abstract

This paper presents a comparison between direct and recursive prediction strategies. In order to perform the input selection, an approach based on mutual information is used. The mutual information is computed between all the possible input sets and the outputs. Least Squares Support Vector Machines are used as non-linear models to avoid local minima problems. Results are illustrated on the Poland electricity load benchmark and they show the superiority of the direct prediction strategy.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:1679
Deposited By:Amaury Lendasse
Deposited On:28 November 2005