关键词: 支持向量机, ART-SVM算法, SOM-SVM算法, 聚类

Abstract: This paper presents two Support Vector Machine（SVM） training algorithms based on Adaptive Resonance Theory（ART） and Self-Organizing feature Map（SOM） neural networks，namely ART-SVM algorithm and SOM-SVM algorithm respectively，in order to improve learning efficiency of SVM on large scale datasets.By clustering the original data，the given data can be reduced greatly.In so doing，the speed of SVM training can be greatly improved and the satisfactory generalization performance can be obtained as well.

Key words: Support Vector Machine（SVM）, ART-SVM algorithm, SOM-SVM algorithm, cluster