The Application of Support Vector Machines in Pattern Regcognition and Regression Models

Support Vector Machines(SVM)are a new kind of novel machine learning methods,based on statistical learning theory,which have become the hotspot of machine learning because of their excellent learning performance.The method of support vector machines has been developed for solving classificationand regression problems.In this paper,the mathematical foundation of SVM and the status in quo are introduced,and several applied algorithms are presented.Some limitations and future research issues are also discussed.