Text classifier based on fuzzy support vector machine and decision tree

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Text classifier based on fuzzy support vector machine and decision tree

Received:2008-07-03 Revised:2008-08-19 Online:2008-12-01 Published:2008-12-01
Contact: Jie Yang

基于模糊支持向量机与决策树的文本分类器

张秋余竭洋李凯

兰州理工大学计算机与通信学院兰州理工大学计算机与通信学院兰州理工大学计算机与通信学院

通讯作者: 竭洋

Abstract

Abstract: For determining the membership function in text classification with fuzzy support vector machine, a construction approach of text classifier based on fuzzy support vector machine and decision tree was proposed. The relationship between the sample and its cluster center was considered and the tangent sphere was constructed by the hyperplane that contained the support vectors and paralleled the classification hyperplane in traditional support vector machine, so to further determine the relation of all samples in the class. The membership of one sample to a class could be computed by the location of the sample in the sphere, so the efficient samples, noises and outliers could be distinguished rationally. Integrating the decision tree method, the classification of multi-classes was realized. The experimental results demonstrate the method has preferable classification effect.

Key words: fuzzy support vector machine, text classification, membership, decision tree

摘要： 针对模糊支持向量机在文本分类应用中的隶属度函数确定问题，提出了一种基于模糊支持向量机与决策树的文本分类器的构建方法。该方法不仅考虑了样本与类中心之间的关系，还根据传统支持向量机中包含支持向量且平行于分类面的平面构建切球,来确定类中各个样本之间的关系，由样本点与球的位置关系计算其隶属度，可以合理地区分有效样本和噪音、孤立点样本。并与决策树方法相结合，实现多类分类。实验结果表明,该方法具有良好的分类效果。

关键词: 模糊支持向量机, 文本分类, 隶属度, 决策树

ZHANG Qiu-yu Jie Yang . Text classifier based on fuzzy support vector machine and decision tree[J]. Journal of Computer Applications.

张秋余竭洋李凯. 基于模糊支持向量机与决策树的文本分类器[J]. 计算机应用.

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