DESCRIPTION

Package: e2tree
Title: Explainable Ensemble Trees
Version: 0.1.0
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 = "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 structure. 
             Starting from an ensemble tree model trained through randomForest or XGBoost packages, 'e2tree' is able to explain graphically the relationship structure between 
             the response variable and predictors. The proposed method appears to be useful in all real-world cases where model explaination and interpretation is crucial (i.e. health, finance, etc.). 
License: MIT + file LICENSE
URL: https://github.com/massimoaria/e2tree
BugReports: https://github.com/massimoaria/e2tree/issues
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
Imports:
    dplyr,
    doParallel,
    parallel,
    foreach,
    future.apply,
    ggplot2,
    Matrix,
    partitions,
    purrr,
    tidyr,
    randomForest,
    rpart.plot