Methods for constructing predictor ensembles based on convex combinations

I. M. Borisov; Борисов И. М.; A. A. Dokukin; Докукин А. А.; O. V. Senko; Сенько О. В.

doi:10.31857/S0002338825040064

Methods for constructing predictor ensembles based on convex combinations

Авторлар: Borisov I.M.¹, Dokukin A.A.², Senko O.V.²
Мекемелер:
1. Lomonosov Moscow State University
2. Computer Science and Control Federal Research Center of the Russian Academy of Sciences
Шығарылым: № 4 (2025)
Беттер: 94-102
Бөлім: COMPUTER METHODS
URL: https://journals.eco-vector.com/0002-3388/article/view/689840
DOI: https://doi.org/10.31857/S0002338825040064
EDN: https://elibrary.ru/BOTSEI
ID: 689840

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Аннотация

Сonstructing convex combinations of predictors is an effective method for building ensembles in solving regression problems. Herewith it seems possible to improve the final quality of the algorithm if an initial set of predictors is constructed in a special way. In this paper, we study two techniques that allow us to achieve such an improvement: bagging in combination with the random subspace method, and optimization of the divergence of predictors. The effectiveness of resulting methods is verified in applied problems.

Негізгі сөздер

regression problem, convex combination of predictors, ensemble divergence optimization

Толық мәтін

Әдебиет тізімі

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