An?Improved?SVM?Multiclass?Classification?Algorithm?Based?on?DAG

doi:10.3969/j.issn.1674-0696.2009.05.39

Journal of Chongqing Jiaotong University(Natural Science) ›› 2009, Vol. 28 ›› Issue (5): 973-975.DOI: 10.3969/j.issn.1674-0696.2009.05.39

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An?Improved?SVM?Multiclass?Classification?Algorithm?Based?on?DAG

WANG Xiao-feng

Department?of?Mathematics,?Bohai?University,?Liaoning?Jinzhou?121013,?China

Received:2009-05-15 Revised:2009-06-18 Online:2009-10-15 Published:2015-04-15

一种改进的有向无环图支持向量机分类算法

王晓锋

渤海大学数学系,辽宁锦州121013

作者简介:王晓锋(1977—),男,辽宁沈阳人,讲师,硕士,主要从事机器学习领域的研究工作。E-mail:w200888w@163.com。
基金资助:
辽宁省教育厅项目( 2008Z018)

Abstract

Abstract: Aiming?at?the?problem?that?the?SVM?multiclass?classification?algorithm?based?on?DAG?doesn＇t?use?an?effective?constructing?algorithm?of?directed?acyclic?graph,?an?improved?SVM?multiclass?classification?algorithm?based?on?DAG?is?put?forward.?The?class?distance?of?clustering?is?taken?as?the?basis?of?hierarchical?classification.?The?experiment?results?show?that?the?new?method?has?higher?classification?accuracy?than?the?original?algorithm?does.

Key words: supporting vector machines（SVG） , clustering , directed acyelic graph（DAG） , multiclass classification

摘要： 针对有向无环图支持向量机多类分类方法未采用有效的有向无环图生成算法,提出了一种改进的有向无环图生成算法。该方法采用了聚类分析中类距离的思想作为层次分类依据。实验结果表明,该方法与原方法相比具有较高的分类精度。

关键词: 支持向量机, 聚类, DAG, 多类分类

CLC Number:

TP391

WANG Xiao-feng. An?Improved?SVM?Multiclass?Classification?Algorithm?Based?on?DAG[J]. Journal of Chongqing Jiaotong University(Natural Science), 2009, 28(5): 973-975.

王晓锋. 一种改进的有向无环图支持向量机分类算法[J]. 重庆交通大学学报（自然科学版）, 2009, 28(5): 973-975.

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An?Improved?SVM?Multiclass?Classification?Algorithm?Based?on?DAG

一种改进的有向无环图支持向量机分类算法

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