【作者】 赵晶； 高隽； 张旭东； 谢昭；

【Author】 Zhao Jing Gao Jun Zhang Xudong Xie Zhao (Image Information Processing Lab., School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009)

【机构】 合肥工业大学计算机与信息学院图像信息处理研究室；

【摘要】 支持向量机是基于统计学习理论的一种新型的机器学习方法,该方法以其优秀的性能获得了越来越广泛的应用。作为对支持向量机的综述介绍,本文首先给出最优超平面的概念,接着引出非线性情况下的支持向量机,并介绍其算法和应用,最后指出它的优点及局限。更多还原

【Abstract】 Support vector machine is a new method of machine learning based on statistical learning theory. Because of its good performance, support vector machine has been used more and more widely. As a brief summary, this article begins with the concept of optimal hyperplane, then we introduce support vector machine for nonlinear case; afterwards, some algorithms of this method are provided here. At last, we summarize its advantages and limitations.更多还原