An Incremental Learning Algorithm of Multiple Support Vector Machines

摘要：

Based on analyzing the construction process of HTSVM, this paper proposes incremental learning algorithm of multi-class SVM based on Huffman tree. This method is to convert the incremental learning of multi-class SVM into the incremental learning of twoclass SVM. Firstly, construct the multi-class SVM based on Huffman tree according to original training datasct. Then, according to the structure of HT-SVM, the new adding dataset is divided into multiple intersection subsets of two-class (If there are k classes of the training dataset, the number of the multiple intersection subsets of two-class is k-1). Finally, the k-1 subsets is send to k-1 two-class classifiers of HT-SVM to be learn using incremental learning algorithm of two-class SVM. Simulate with KDD CUP 1999 dataset, and the experiment results show the performance.

关键词： Support Vector Machine Incremental Learning KKT Theory Separation measure

作者: Hongle DU Aijun LIU Jing CAO

作者单位: Department of Computer Science.Shangluo University shangluo,726000,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 14-18

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）