Comparison between two solving methods for smooth support vector machine
光滑支持向量机两种求解算法的比较

The BFGS-Armijo method and Newton-Armijo method are two popular methods to solve the smooth models. The authors respectively listed the procedures of these two methods to solve Smooth Support Vector Machine (SSVM), and made a comparative study between the two methods to solve SSVM. The numerical results show that the classification performance of BFGS-Armijo method is almost the same as the Newton-Armijo method, but the classification efficiency of Newton-Armijo method is 26.2% higher than that of BFGS-Armijo method.