A Two-Stage Method for Constructing Linear Regressions Using Optimal Convex Combinations
- Авторлар: Senko O.1, Dokukin A.1, Kiselyova N.2, Khomutov N.1
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Мекемелер:
- Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control”
- Baikov Institute of Metallurgy and Materials Science
- Шығарылым: Том 97, № 2 (2018)
- Беттер: 113-114
- Бөлім: Mathematics
- URL: https://journals.rcsi.science/1064-5624/article/view/225470
- DOI: https://doi.org/10.1134/S1064562418020035
- ID: 225470
Дәйексөз келтіру
Аннотация
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.
Авторлар туралы
O. Senko
Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control”
Email: dalex@ccas.ru
Ресей, Moscow, 119333
A. Dokukin
Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control”
Хат алмасуға жауапты Автор.
Email: dalex@ccas.ru
Ресей, Moscow, 119333
N. Kiselyova
Baikov Institute of Metallurgy and Materials Science
Email: dalex@ccas.ru
Ресей, Moscow, 119991
N. Khomutov
Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control”
Email: dalex@ccas.ru
Ресей, Moscow, 119333