J4 ›› 2010, Vol. 37 ›› Issue (1): 136-141.doi: 10.3969/j.issn.1001-2400.2010.01.024

• 研究论文 • 上一篇    下一篇



  1. (1. 西安电子科技大学 理学院,陕西 西安  710071;
    2. 西北大学 信息技术学院,陕西 西安  710069)
  • 收稿日期:2009-04-13 出版日期:2010-02-20 发布日期:2010-03-29
  • 通讯作者: 常甜甜
  • 作者简介:常甜甜(1981-),女,西安电子科技大学博士研究生,E-mail: changtiantian@gmail.com.
  • 基金资助:


Support vector machine ensemble learning algorithm research based on heterogeneous data

CHANG Tian-tian1;LIU Hong-wei1;FENG Jun2   

  1. (1. School of Science, Xidian Univ., Xi'an  710071, China;
    2. School of Information Sci. and Tech., Northwest Univ., Xi'an  710069, China)
  • Received:2009-04-13 Online:2010-02-20 Published:2010-03-29
  • Contact: CHANG Tian-tian



关键词: 集成学习, 支持向量机, 多源性, 医学图像


An SVM ensemble learning algorithm based on grouped features is proposed for heterogeneous data. The feature is grouped and trained with different SVM classifiers, and then the final predict labels are obtained by the voting method. The diversity component classifiers with higher classification performance are obtained. Experimental results show that, compared with traditional ensemble learning, this method has the best performance.

Key words: ensemble learning, support vector machine, heterogeneous, medical image