Package: e2tree
Title: Explainable Ensemble Trees
Version: 1.0.0
Authors@R: c(
    person(given = "Massimo",
           family = "Aria",
           role = c("aut", "cre", "cph"),
           email = "aria@unina.it",
           comment = c(ORCID = "0000-0002-8517-9411")),
           person(given = "Agostino",
           family = "Gnasso",
           role = c("aut"),
           email = "agostino.gnasso@unina.it",
           comment = c(ORCID = "0000-0002-8046-3923"))
           )
Description: The Explainable Ensemble Trees 'e2tree' approach has been proposed by Aria et al. (2024) <doi:10.1007/s00180-022-01312-6>. It aims to explain and interpret decision tree ensemble models using a single tree-like structure. 'e2tree' is a new way of explaining an ensemble tree trained through 'randomForest' or 'xgboost' packages.
License: MIT + file LICENSE
URL: https://github.com/massimoaria/e2tree
BugReports: https://github.com/massimoaria/e2tree/issues
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: ape, dplyr, parallel, future.apply, ggplot2, Matrix,
        partitions, purrr, tidyr, Rcpp
LazyData: true
LinkingTo: Rcpp
Suggests: doParallel, foreach, htmlwidgets, jsonlite, randomForest,
        ranger, rpart.plot, RSpectra, testthat (>= 3.0.0), visNetwork
Config/testthat/edition: 3
Depends: R (>= 3.5)
NeedsCompilation: yes
Packaged: 2026-03-13 17:28:52 UTC; massimoaria
Author: Massimo Aria [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-8517-9411>),
  Agostino Gnasso [aut] (ORCID: <https://orcid.org/0000-0002-8046-3923>)
Maintainer: Massimo Aria <aria@unina.it>
Repository: CRAN
Date/Publication: 2026-03-13 17:50:02 UTC
Built: R 4.5.3; x86_64-w64-mingw32; 2026-04-22 03:16:25 UTC; windows
Archs: x64
