华东师范大学学报(自然科学版) ›› 2013, Vol. 2013 ›› Issue (3): 209-218.

• 电子科学与计算机科学 • 上一篇    

基于类间可分性DAG-SVM的文本分类

黄振龙， 郑 骏， 胡文心   

  1. 华东师范大学 计算中心,上海 200062
  • 收稿日期:2012-05-01 修回日期:2012-08-01 出版日期:2013-05-25 发布日期:2013-07-10

Text classification based on inter-class separability DAG-SVM

HUANG Zhen-long, ZHENG Jun, HU Wen-xin   

  1. Computer Center, East China Normal University, Shanghai 200062, China
  • Received:2012-05-01 Revised:2012-08-01 Online:2013-05-25 Published:2013-07-10

PDF

2346

摘要： 本方法采用了以类间分布和类间中心距离作为依据，对有向无环图结构进行调整，以解决传统的DAG-SVM多分类结构固定、单个节点位置随意引起的“误差累积”严重的缺陷.实验表明，该改进后的DAG-SVM文本分类方法，对文本分类准确率有一定的提高.

关键词: 文本分类, 支持向量机, DAG-SVM, 类间可分性

Abstract: This paper took an improved algorithm based on inter-class separability directed acyclic graph support vector machine (DAG-SVM) for text classification.The method has adjusted the DAG structure according to inter-class distribution and the distance between centers. It has solved the problems of fixed structure and random single node location in traditional DAG-SVM multi-classification method.The experiments show that the algorithm has improved the accuracy.

Key words: text classification, support vector machine, DAG-SVM, inter-class separability

中图分类号: