RIVAL变量选择

22nd Mediterranean Conference on Control and Automation Pub Date : 2014-06-16 DOI:10.1109/MED.2014.6961490

E. Bai, Kang Li, P. Kump

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摘要

本文考虑了变量选择问题，提出了一种名为RIVAL(在Lasso迭代中去除无关变量)的算法。对于给定且固定长度的数据点，该算法递归地更新权重，从而大大提高了算法检测零系数的能力。数值模拟结果支持了理论收敛性的建立。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Variable selection by RIVAL

The paper considers variable selection problem and proposes an algorithm called the RIVAL (Removing Irrelevant Variables Amidst Lasso Iterations). For a given and fixed length of data points, the algorithm recursively updates the weights so that the ability of the algorithm in detecting zero coefficients is substantially improved. Theoretical convergence is established supported by numerical simulation results.

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22nd Mediterranean Conference on Control and Automation

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