LS SVMs Classification Algorithm of   Iterative Reweighted q-norm Regularization

doi:10.3969/j.issn.1000-3428.2012.03.056

Computer Engineering ›› 2012, Vol. 38 ›› Issue (3): 166-168.

• Networks and Communications • Previous Articles Next Articles

LS SVMs Classification Algorithm of Iterative Reweighted q-norm Regularization

LIU Jian-wei, LI Shuang-cheng, LUO Xiong-lin

(Research Institute of Automation, China University of Petroleum, Beijing 102249, China)

Received:2011-07-21 Online:2012-02-05 Published:2012-02-05

迭代再权q范数正则化LS SVM分类算法

刘建伟，李双成，罗雄麟

(中国石油大学自动化研究所，北京 102249)

作者简介:刘建伟(1966－)，男，副研究员、博士，主研方向：机器学习；李双成，硕士研究生；罗雄麟，教授、博士

Abstract

Abstract: This paper proposes the classification algorithm of fast iterative reweighted q-norm regularization Least Squares Support Vector Machine(LS SVM). The proposed algorithm can select q value via cross-validation, where 0

Key words: iterative reweighted method, q-norm, Least Squares Support Vector Machine(LS SVM), regularization, feature selection, classification algorithm

摘要： 提出一种迭代再权q范数正则化最小二乘支持向量机(LS SVM)分类算法。该算法通过交叉校验过程选择正则化范数的阶次q (0

关键词: 迭代再权方法, q范数, 最小二乘支持向量机, 正则化, 特征选择, 分类算法

CLC Number:

TP301.6

LIU Jian-Wei, LI Shuang-Cheng, LUO Xiong-Lin. LS SVMs Classification Algorithm of Iterative Reweighted q-norm Regularization[J]. Computer Engineering, 2012, 38(3): 166-168.

刘建伟, 李双成, 罗雄麟. 迭代再权q范数正则化LS SVM分类算法[J]. 计算机工程, 2012, 38(3): 166-168.

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https://www.ecice06.com/EN/Y2012/V38/I3/166

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