Multiple SVMs Enabled Sales Forecasting Support System.

This paper proposes a multiple SVMs enabled sales forecasting support system (SFSS). The SFSS has a two-stage system architecture. In the first stage, agglomerative hierarchical clustering(AHC) is used to partition the goods into several patterns based on similarity measure. In the second stage, multiple SVMs that best fit partitioned patterns are constructed by finding the appropriate kernel function and the optimal free parameters of SVMs. The experiment shows that this integrated system achieves significant improvement in forecasting performance compared with single SVMs models. [ABSTRACT FROM AUTHOR]