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一种改进的半监督增量SVM学习算法

An Refinement Algorithm of Semisupervised-incremental SVM Learning
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摘要 通过分析现有SVM的两种改进算法:半监督学习算法和增量学习算法,给出了对现有的增量学习算法的改进,提出了一种新的半监督增量SVM学习算法,将其应用于Web文本分类中,并验证了半监督增量SVM学习算法的有效性和可行性。 SVM has a good performance in pattern classification.According to the analysis of the two present refinement algorithms about SVM:Semisupervised Learning and Incremental Learning,an improved algorithm of present Incremental Learning algorithm is gavn.A new algorithm of semisupervised-Incremental SVM learning is given out.Also this new algorithm is used in Web text classification.
作者 吕宏伟
机构地区 武警工程学院
出处 《科学技术与工程》 2010年第1期238-240,共3页 Science Technology and Engineering
基金 国家科技部高新司项目(2005EJ000006)资助
关键词 支持向量机 半监督学习 增量学习 WEB文本分类 SVM semisupervised learning incremental learning Web text classification
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参考文献4

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  • 2Burges C J C. A tutorial on support vector machines for pattern recognition. Knowledge Discovery and Data Mining, 1998 ;2(2) :121-167.
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  • 4Cristianini N, Shawe-Taylor J. An introduction to support vector machines and other Kernel-based learning Methods. Publishing House of Electronics Industry, 2004.

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