Discussion on the Relation Between SVM Training Sample Size and Correct Forecast Ratio for Simulation Experiment Results

A series of support vector machine (SVM) forecast experiments are carried out to reveal the relation between the SVM training sample size and SVM correct forecast ratio for simulation experiment results. Experiment results show that the SVM correct forecast ratio increases to some extent with the number of training samples becoming more and then keeps unchanged even if the SVM training sample number increases further. And SVM has also been proved to be able to overcome the over-fitting issue always afflicting Back-Propagation Neural Networks (BPNN).