Information System Establishment and Prediction Analysis for SVM Model of RBF Kernel Function

Abstract

The effective prediction of Shanghai Composite Index can provide much useful information for relative organizations to analyze the changes of stock market and then make right decision. Therefore, the prediction of the Shanghai Composite Index is meaningful. In this study, supported vector machine (SVM) algorithm is employed to construct the prediction model, and MSE R2 are used for error test. The result shows SVM model has high accuracy, which indicates the prediction model established in this study is reliable.