支持向量机处理大规模问题算法综述

Survey of Applying Support Vector Machines to Handle Large-scale Problems

支持向量机在处理大规模问题时存在训练时间过长和内存空间需求过大的问题。分析了支持向量机在处理大规模问题时存在的局限性;对利用支持向量机处理大规模问题的各种算法进行了分类,并对每种算法的研究状况进行了较全面而深入的综述;对该领域内值得进一步研究的问题进行了讨论。

Being applied to handling large-scale problems, support vector machines（SVMs） needs longer training time and larger memory. The paper analyzed the limitation of SVMs, classified the algorithms of applying SVMs to handle large-scale problems into seven types, and made profound and comprehensive analysis of each kind of algorithm. Moreover, some issues valuable for future exploration in this area were indicated and discussed.