Selection and Application of Support Vector Machine

This paper introduces the selection and application of kernel functions of support vector machine (SVM) and their parameters. The recent researches on SVM and its application are reviewed. Simulation experiment is conducted under different learning methods, and the classification properties of 4 learning methods are analyzed and compared. The selection condition of different learning methods for different pattern recognition are given at the end of the paper.