Hybrid sparse regression algorithm
DOI: 10.21293/1818-0442-2025-28-1-86-92
Abstract: A hybrid algorithm to construct sparse regression is proposed. The proposed algorithm was tested using real and synthetic data. The experimental results demonstrate the applicability of the proposed algorithm to the tasks under consideration and show its efficiency compared to known methods.
Keywords: sparse regression, Lasso, feature selection, inverse problem
Funding: This study was supported by the Russian Science Foundation (project No. 25-21-00123).
For citation:
Gribanova E. B., Gerasimov R. S. Hybrid sparse regression algorithm. Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki, 2025, vol. 28, no. 1, pp. 86–92. DOI: 10.21293/1818-0442-2025-28-1-86-92
Authors and copyright holders:
- Gribanova E. B. , Tomsk State University of Control Systems and Radioelectronics (Tomsk, Russia)
- Gerasimov R. S. , Tomsk State University of Control Systems and Radioelectronics (Tomsk, Russia)
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