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randomMachines: An Ensemble Modeling using Random Machines
A novel ensemble method employing Support Vector Machines (SVMs) as base learners. This powerful ensemble model is designed for both classification (Ara A., et. al, 2021) <doi:10.6339/21-JDS1014>, and regression (Ara A., et. al, 2021) <doi:10.1016/j.eswa.2022.117107> problems, offering versatility and robust performance across different datasets and compared with other consolidated methods as Random Forests (Maia M, et. al, 2021) <doi:10.6339/21-JDS1025>.
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Package details |
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| Author | Mateus Maia [aut, cre] (ORCID: <https://orcid.org/0000-0001-7056-386X>), Anderson Ara [cte] (ORCID: <https://orcid.org/0000-0002-1041-2768>), Gabriel Ribeiro [cte] |
| Maintainer | Mateus Maia <mateus.maiamarques@glasgow.ac.uk> |
| License | MIT + file LICENSE |
| Version | 0.1.1 |
| Package repository | View on CRAN |
| Installation |
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