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Incremental Training for SVM-Based Classification with keyword adjusting

Wuhan University Journal of Natural Sciences 2004年第5期9卷 805-811页

作者： SUNJin-wen YANGJian-wu LUBin XIAOJian-guo NationalKeyLaboratoryforTextProcessing.InstituteofComputerScienceandTechnology.PekingUniversity.Beijing100871.China

This paper analyzed the theory of incremental learning of SVM (support vector machine) and pointed out it is a shortage that the support vector optimization is only considered in present research of SVM incremental learning. According to the significance of keyword in training, a new incremental training method considering keyword adjusting was proposed, which eliminates the difference between incremental learning and batch learning through the keyword adjusting. The experimental results show that the improved method outperforms the method without the keyword adjusting and achieve the same precision as the batch method. Key words SVM (support vector machine) - incremental training - classification - keyword adjusting CLC number TP 18 Foundation item: Supported by the National Information Industry Development Foundation of ChinaBiography: SUN Jin-wen (1972-), male, Post-Doctoral, research direction: artificial intelligence, data mining and system integration.

关键词： SVM (support vector machine) incremental training classification keyword adjusting

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Incremental Training for SVM-Based Classification with keyword adjusting

Incremental Training for SVM-Based Classification with Keywo...

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The First Conference on Web Information System and Applications

作者： SUN Jin-wen, YANG Jian-wu, LU Bin, XIAO Jian-guo National Key Laboratory for Text Processing, Institute of Computer Science and Technology, Peking University, Beijing 100871, China

＜正＞ This paper analyzed the theory of incremental learning of SVM （support vector machine） and pointed out it is a shortage that the support vector optimization is only considered in present research of SVM incremental learning. According to the significance of keyword in training, a new incremental training method considering keyword adjusting was proposed, which eliminates the difference between incremental learning and batch learning through the keyword adjusting. The experimental results show that the improved method outperforms the method without the keyword adjusting and achieve the same precision as the batch method.

关键词： SVM(support vector machine) incremental training classification keyword adjusting

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