支持向量机研究

Research of Support Vector Machines

支持向量机是一类新型机器学习方法，由于其出色的学习性能，该技术已成为当前国际机器学习界的研究热点。该文首先引入最优超平面的概念，然后对线性ＳＶＭｓ和非线性ＳＶＭｓ进行介绍，给出一些常用的训练算法，并指出ＳＶＭｓ存在的局限和将来可能的研究内容。

Support Vector Machines are a kind of novel machine learning methods,which have become the hotspot of machine learning because of their excellent learning performance. In this paper,linear and nonlinear SVMs are introduced based on the notion of optimal margin hyperplane,several popular training algorithms are presented,and some limitations and future research issues are also discussed.