A generalized Gilbert algorithm and an improved MIES for one-class support vector machine

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A generalized Gilbert algorithm and an improved MIES for one-class support vector machine

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作者：Ming Zeng^a ; ^b ; ^{zeng_m@126.com" class="auth_mail" title="E-mail the corresponding author} ; Yu Yang^a ; ^b ; ^{yangyu@hnu.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Junsheng Cheng^a ; ^b ; ^{signalp@tom.com" class="auth_mail" title="E-mail the corresponding author}
关键词：One-class support vector machine ; Generalized Gilbert algorithm ; Reduced convex hull ; Gaussian kernel ; Parameter selection
刊名：Knowledge-Based Systems
出版年：2015
出版时间：December 2015
年：2015
卷：90
期：Complete
页码：211-223
全文大小：1038 K

文摘

•: The primal maximum margin problem of OCSVM is equivalent to a nearest point problem.
•: A generalized Gilbert (GG) algorithm is proposed to solve the nearest point problem.
•: An improved MIES is developed for the Gaussian kernel parameter selection.
•: The GG algorithm is computationally more efficient than the SMO algorithm.

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