Constructive analysis for coefficient regularization regression algorithms

Constructive analysis for coefficient regularization regression algorithms
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系数正则化回归算法的建设性分析

DOI:
10.1016/j.jmaa.2015.06.006
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发表时间:
2015-11-15
影响因子:
1.3
通讯作者:
Wang, Cheng
Wang, Cheng
中科院分区:
数学3区
文献类型:
--
作者:
Nie, Weilin;Wang, Cheng

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在本文中,我们考虑了具有广义系数正则化项的最小二乘回归算法。引入了涉及建设性垫脚石功能的新型误差分解。通过为建设性函数选择适当的参数,我们最终在某种条件下得出了令人满意的学习率,以实现假设空间的目标函数和能力。 (c)2015 Elsevier Inc.保留所有权利。
In this paper, we consider the least squares regression algorithm with a generalized coefficient regularization term. A novel error decomposition involving a constructive stepping-stone function is introduced. By choosing appropriate parameters for the constructive function we finally derive a satisfactory learning rate under some condition for the goal function and capacity of the hypothesis space. (C) 2015 Elsevier Inc. All rights reserved.