A Two-Stage Method for Constructing Linear Regressions Using Optimal Convex Combinations
- 作者: Senko O.V.1, Dokukin A.A.1, Kiselyova N.N.2, Khomutov N.Y.1
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隶属关系:
- Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control”
- Baikov Institute of Metallurgy and Materials Science
- 期: 卷 97, 编号 2 (2018)
- 页面: 113-114
- 栏目: Mathematics
- URL: https://journals.rcsi.science/1064-5624/article/view/225470
- DOI: https://doi.org/10.1134/S1064562418020035
- ID: 225470
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详细
Multilevel learning systems have become more popular in pattern recognition and regression analysis. In this paper, a two-level method for constructing a multidimensional regression model is considered, in which a family of optimal convex combinations of simple one-dimensional least-square regressions is generated at the first level. The second level of the proposed learning system is given by an elastic net. Experimental verification presented demonstrate the efficiency of the proposed regression estimation method as applied to problems with a small amount of data.
作者简介
O. Senko
Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control”
Email: dalex@ccas.ru
俄罗斯联邦, Moscow, 119333
A. Dokukin
Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control”
编辑信件的主要联系方式.
Email: dalex@ccas.ru
俄罗斯联邦, Moscow, 119333
N. Kiselyova
Baikov Institute of Metallurgy and Materials Science
Email: dalex@ccas.ru
俄罗斯联邦, Moscow, 119991
N. Khomutov
Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control”
Email: dalex@ccas.ru
俄罗斯联邦, Moscow, 119333
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