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ν-支持向量机的收敛性

Convergence of ν-support vector machine
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摘要 支持向量机是在统计学习理论最新发展的基础上产生的一个崭新的学习系统.支持向量机算法通过支持向量控制学习机器的容量.为了控制支持向量的数目,Schφlkopf等提出了ν-支持向量机.研究了ν-支持向量机的若干性质,并给出了相应算法的收敛性. Support vector machine is a new learning system based on statistical learning theory. Support vector machine algorithms control the capacity of learning machine by support vectors. Schφlkopf et al. introduced v-support vector machine to control the number of support vectors, the properties of v-support vector machine and the convergence of corrvergence of corresponding algorithm are studied.
作者 蔡佳 陈洪
出处 《湖北大学学报(自然科学版)》 CAS 北大核心 2005年第4期321-325,共5页 Journal of Hubei University:Natural Science
基金 国家自然科学基金(10371033)资助课题
关键词 V-支持向量机 错分误差 再生核希尔伯特空间 v-support vector machine misclassification error reproducing kernel Hilbert space
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参考文献9

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