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>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 2.10) |
| Imports: |
kernlab, methods, stats |
| Published: |
2023-12-14 |
| DOI: |
10.32614/CRAN.package.randomMachines |
| Author: |
Mateus Maia  [aut,
cre] (<https://orcid.org/0000-0001-7056-386X>),
Anderson Ara
[cte] (<https://orcid.org/0000-0002-1041-2768>),
Gabriel Ribeiro [cte] |
| Maintainer: |
Mateus Maia <mateus.maiamarques.2021 at mumail.ie> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
randomMachines results |
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