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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。
SVM is a new type of machine learning method. Due to its excellent learning performance, SVM technology has become a hot research topic in the current international machine learning community. Firstly, the concept of optimal hyperplane is introduced. Then, linear SVMs and nonlinear SVMs are introduced. Some commonly used training algorithms are given. The limitations of SVMs and possible future research contents are also pointed out.