Package: randomMachines
Type: Package
Title: An Ensemble Modeling using Random Machines
Version: 0.1.1
Authors@R: c(person("Mateus", "Maia", email = "mateus.maiamarques@glasgow.ac.uk", role = c("aut","cre"), comment = c(ORCID = "0000-0001-7056-386X")),
            person("Anderson", "Ara", email = "ara@ufpr.br", role = c("cte"), comment = c(ORCID = "0000-0002-1041-2768")),
            person("Gabriel", "Ribeiro", email = "brielribeiro08@gmail.com", role = c("cte")))
Description: 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>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
Imports: kernlab, methods, stats
Depends: R (>= 2.10)
Suggests:
NeedsCompilation: no
Packaged: 2025-07-23 12:46:58 UTC; mm538r
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>
Repository: CRAN
Date/Publication: 2025-07-23 13:20:10 UTC
Built: R 4.6.0; ; 2026-04-25 21:32:30 UTC; unix
