Variable Scaling for Time Series Prediction
Francesco Corona, Amaury Lendasse · 2007
Abstract. In this paper, variable selection and variable scaling are used in order to select the best regressor for the problem of time series prediction. Direct prediction methodology is used instead of the classic recursive methodology. Least Squares Support Vector Machines (LS-SVM) are used in order to avoid local minimal in the training phase of the model. The global methodology is applied to the time series competition dataset. 1