Package: BORT
Type: Package
Title: Beyond Pareto: Bi-Objective and Multi-Objective Regression
        Trees’
Version: 0.1.0
Authors@R: c(person(given = c("Erick", "G.G."),
                      family = "de Paz",
                      role = c("aut", "cre"),
                      email = "erick.giles@cimat.mx",
                      comment = c(ORCID = "0000-0001-7878-8238")),
               person(given = "Arturo",
                      family = "Hernández-Aguirre",
                      role = "aut",
                      comment = c(ORCID = "0000-0002-3744-9827")),
               person(given = "Iván",
                      family = "Cruz-Aceves",
                      role = "aut",
                      comment = c(ORCID = "0000-0002-5197-2059")))
Author: Erick G.G. de Paz [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-7878-8238>),
  Arturo Hernández-Aguirre [aut] (ORCID:
    <https://orcid.org/0000-0002-3744-9827>),
  Iván Cruz-Aceves [aut] (ORCID: <https://orcid.org/0000-0002-5197-2059>)
Maintainer: Erick G.G. de Paz <erick.giles@cimat.mx>
Description: Implements the Bi-objective Regression Tree (BORT) for efficiently 
    learning vector-valued functions. Unlike traditional methods that rely on 
    constructing multiple models or static scalarisation, BORT integrates the 
    exploration of the Pareto front directly into a single tree's growth process. 
    It provides high-efficiency, single-model approaches that can Pareto-dominate 
    entire Pareto-consistent families of trees, supported by a C backend for 
    fast computation. For more details see 
    Paz (2026) <doi:10.1007/978-3-032-28393-1_2> and
    Paz (2025) <doi:10.1007/978-3-031-78401-9_2>.
License: GPL-2
Encoding: UTF-8
NeedsCompilation: yes
Repository: CRAN
Date: 2026-07-01
Depends: R (>= 2.10.0)
Packaged: 2026-07-01 23:27:53 UTC; erick
Date/Publication: 2026-07-07 09:50:08 UTC
