Journal of Jilin University Science Edition
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ZHOU Xiaotang, OUYANG Jihong, LI Ximing
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Empirical risk minimization inductive principle and gradient descent method were used to fix classcentroidvectors in traditional centroidbased text classification algorithms so as to improve the poor expression ability of classcentroidvectors in traditional centroidbased text classification algorithm caused by ignoring the weighting factors of training texts. Then, an improved centroidbased text classification algorithm was obtained, the performance of which is as well as those of support vector machines. Experimental results show that the method adopted in this article is an effective mean to improve the performance of traditional centroidbased text classification algorithms.
Key words: text classification, centroidbased text classification algorithms, empirical risk minimization
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ZHOU Xiaotang, OUYANG Jihong, LI Ximing. Centroid Classifier Based on Empirical Risk for Text Categorization[J].Journal of Jilin University Science Edition, 2013, 51(05): 876-880.
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http://xuebao.jlu.edu.cn/lxb/EN/Y2013/V51/I05/876
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