Evaluation Method and Application Based on Rough Set-Support Vector Regression Model
Wang Xiu, Xing Zhang, Chong Gao · 2009
Support Vector Machine has the convenient superiority in the classification. Recently it has been extended to the domain of regression problems. However, due to the increasing index, excess input data and complicated system structure, it is difficult to achieve good accuracy in results. This paper adopts combination method of rough set and support vector machine so as to establish rough set attribute reducing support vector regression model to carry out the comprehensive evaluation of the innovative talents training in engineering universities. The experimental results show that this method has strong objectivity and impartiality, and can increase the computing speed.