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

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

中图分类号: 

• TP301.6