基于1-a-r和多约束的多类文本分类算法

Yu-ping Qin, Fengfeng Qin, Q. Leng, Aihua Zhang
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引用次数: 0

摘要

针对多类文本分类问题,提出了一种基于多约束和1-a-r方法的分类算法。采用1-a-r方法将一个多类分类问题转化为若干个二元分类问题。在输入空间中,对每一个二进制问题都构造了多并行控制器。对于要分类的文本,其类别由多控制器决定。在路透社21578上进行了分类实验。实验结果表明,与1-a-r支持向量机相比,该算法具有更好的分类性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On multiclass text classification algorithm based on 1-a-r and multiconlitron
Aim to multiclass text categorization problem, a classification algorithm based on multiconlitron and 1-a-r method is presented. 1-a-r method is used to convert a multiclass categorization problem to several binary problems. Multiconlitron is constructed for each binary problem in input space. For the text to be classified, its class is decided by multiconlitrons. The classification experiments are made on the Reuters 21578. Experimental results indicate that the proposed algorithm has better classification performance compare with 1-a-r SVMs.
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