支持向量机理论的研究与进展

Research and Development of Support Vector Machine Theory

摘要:

回顾了支持向量机理论的发展历程,介绍了支持向量机的标准训练算法及其分解算法、变形算法、几何算法以及多类分类算法,重点描述了最小二乘支持向量机算法,总结了支持向量机理论及其应用的现状与存在问题,对支持向量机的未来发展方向进行了展望。

Abstract:

The development history of support vector machine (SVM) was reviewed. The standard training algorithm, decomposition algorithm, transmutation algorithm, geometry algorithm and multi-class classifier algorithm of SVM were introduced. The Least Square (LS) SVM algorithm was described in detail. The research actuality and existent problems of SVM theory and its applications were summarized and the future development direction of SVM theory was expected.