Survey of Recent Trends in Local Support Vector Machine
局部支持向量机的研究进展

Support Vector Machine(SVM) is an important and widely used classifier. If a sample wants to be classified,all training data will be used to obtain a hyperplane which is used to determine the label of that sample, that is, the SVM worked in global manner. However, this global behaviour doesn't imply consistency. hhe design of Local SVM(I_SVM)is in accordance with the result of"consistency implies local behaviour". In this paper, we first reviewed the main idea of LSVM, followed by the improvements on LSVM. In the following, we presented an LSVM algorithm which is based on cooperative clustering,reducing the time complexity of I_SVM in large scaled dataset. Then we ended this article by the conclusion.