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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "BORT" in publications use:'
type: software
license: GPL-2.0-only
title: 'BORT: Beyond Pareto: Bi-Objective and Multi-Objective Regression Trees’'
version: 0.1.0
abstract: 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) <https://doi.org/10.1007/978-3-032-28393-1_2>
  and Paz (2025) <https://doi.org/10.1007/978-3-031-78401-9_2>.
authors:
- family-names: Paz
  given-names: Erick G.G.
  name-particle: de
  email: erick.giles@cimat.mx
  orcid: https://orcid.org/0000-0001-7878-8238
- family-names: Hernández-Aguirre
  given-names: Arturo
  orcid: https://orcid.org/0000-0002-3744-9827
- family-names: Cruz-Aceves
  given-names: Iván
  orcid: https://orcid.org/0000-0002-5197-2059
repository: https://cran.r-universe.dev
commit: 4e8d2a2f68ba5052305edeaf2cde314fa462862c
date-released: '2026-07-01'
contact:
- family-names: Paz
  given-names: Erick G.G.
  name-particle: de
  email: erick.giles@cimat.mx
  orcid: https://orcid.org/0000-0001-7878-8238