| 基于类间可分性DAG-SVM的文本分类 |
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| 引用本文： | 黄振龙,郑骏,胡文心.基于类间可分性DAG-SVM的文本分类[J].华东师范大学学报(自然科学版),2013,2013(3):209-218. |
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| 作者姓名： | 黄振龙 郑骏 胡文心 |
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| 作者单位： | 华东师范大学计算中心,上海,200062 |
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| 基金项目： | 国家863项目，上海市科委重大科技攻关项目 |
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| 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.
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| 关 键 词： | 文本分类 支持向量机 DAG-SVM 类间可分性 |
| 收稿时间： | 2012-05-01 |
Text classification based on inter-class separability DAG-SVM |
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| HUANG Zhen-long
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ZHENG Jun
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HU Wen-xin.Text classification based on inter-class separability DAG-SVM[J].Journal of East China Normal University(Natural Science),2013,2013(3):209-218. |
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| Authors: | HUANG Zhen-long ZHENG Jun HU Wen-xin |
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| Institution: | Computer Center, East China Normal University, Shanghai 200062, China |
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| 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. |
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