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Regression model based on convex combinations best correlated with responseстатья
Информация о цитировании статьи получена из
Web of Science,
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 28 октября 2016 г.
- Авторы: Dokukin A.A., Senko O.V.
- Журнал: Computational Mathematics and Mathematical Physics
- Том: 55
- Номер: 3
- Год издания: 2015
- Издательство: Pleiades Publishing, Ltd
- Местоположение издательства: Road Town, United Kingdom
- Первая страница: 526
- Последняя страница: 539
- DOI: 10.1134/s0965542515030045
- Аннотация: 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.
- Добавил в систему: Журавлев Юрий Иванович