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This article is cited in 2 scientific papers (total in 2 papers)
Regression model based on convex combinations best correlated with response
A. A. Dokukin, O. V. Senko Dorodnicyn Computing Center, Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, ul. Vavilova 40, Moscow, 119333, Russia
Abstract:
A new regression method based on constructing optimal convex combinations of simple linear regressions of the least squares method (LSM regressions) built from original regressors is presented. It is shown that, in fact, this regression method is equivalent to a modification of the LSM including the additional requirement of the coincidence of the sign of the regression parameter with that of the correlation coefficient between the corresponding regressor and the response. A method for constructing optimal convex combinations based on the concept of nonexpandable irreducible ensembles is described. Results of experiments comparing the developed method with the known glmnet algorithm are presented, which confirm the efficiency of the former.
Key words:
regression, convex correction, regularization.
Received: 10.09.2013 Revised: 29.09.2014
Citation:
A. A. Dokukin, O. V. Senko, “Regression model based on convex combinations best correlated with response”, Zh. Vychisl. Mat. Mat. Fiz., 55:3 (2015), 530–544; Comput. Math. Math. Phys., 55:3 (2015), 526–539
Linking options:
https://www.mathnet.ru/eng/zvmmf10179 https://www.mathnet.ru/eng/zvmmf/v55/i3/p530
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Abstract page: | 242 | Full-text PDF : | 90 | References: | 38 | First page: | 6 |
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