SVR Model for Prediction of Incidence Influenza Based on Automated Method

As is a significant public health issue to predict the incidence of influenza, this paper present a supported vector regression (SVR) model based on an automated method which worked as the following steps: firstly, the automated method is used to select the texts which highly related to the influenza, and then the SVR algorithm will find out the nonlinear between each context. According to the result, when assessing by the root mean squared predict error, the mean absolute error and the mean absolute percent error of the whole system, the SVR performed much better than single support vector machine regression prediction. Also, the validity of this method is verified.