计算机应用 ›› 2005, Vol. 25 ›› Issue (11): 2653-2654.

• 人工智能 • 上一篇    下一篇

一种新的基于二叉树的SVM多类分类方法

孟媛媛，刘希玉   

  1. 山东师范大学信息管理学院
  • 收稿日期:1900-01-01 修回日期:1900-01-01 发布日期:2005-11-01 出版日期:2005-11-01
  • 基金资助:

    山东省自然科学基金资助项目(Z2004G02);;山东省中青年科学家奖励基金项目(03BS003)

A new SVM multiclass classification based on binary tree

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  1. College of Information and Management,Shandong Normal University, Jinan Shandong 250014,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2005-11-01 Published:2005-11-01

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摘要： 介绍了几种常用的支持向量机多类分类方法，分析其存在的问题及缺点。提出了一种基于二叉树的支持向量机多类分类方法（BTSVM），并将基于核的自组织映射引入进行聚类。结果表明，采用该方法进行多类分类比1vr SVMs和1v1 SVMs具有更高的分类精度。

关键词: 多类分类, 支持向量机, 二叉树, 自组织映射

Abstract: The problems and defections of the existing methods of SVM multi-class classification were analyzed.A multi-class classification based on binary tree was put forward.A modified self-organization map(SOM),KSOM(kernel-based SOM),was introduced to convert the multi-class problem into binary tress,in which the binary decisions were made by SVMs.The results show that it has higher multiclass classification accuracy than the multi-class SVM approaches with "one-versus-one" and "one-versus-the rest".

Key words: multi-class classification, support vector machine(SVM), binary tree, Self-Organization Map(SOM)

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