DESCRIPTION

Package: endoR
Type: Package
Title: Interpret and Visualize Stable Tree Ensemble Models
Version: 0.1.0
Authors@R: c(person("Albane", "Ruaud", email = "albane.ruaud@tuebingen.mpg.de"
                  , role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5920-1710"))
            , person("Houtao", "Deng", role = "ctb"))
Description: Extract and visualize how predictive variables contribute to tree ensemble model accuracy. 
  You provide the model and data, tell endoR which regularization steps you want to obtain stable results, and it will return a plot of the feature importance and influence on the response variable and a decision network. For more details, please refer to our pre-print:  Albane Ruaud, Niklas A Pfister, Ruth E Ley, Nicholas D Youngblut. Interpreting tree ensemble machine learning models with endoR. bioRxiv (2022). <doi: 10.1101/2022.01.03.474763>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Suggests:
    knitr,
    rmarkdown,
    testthat (>= 3.0.0)
Imports: rlang, data.table, dplyr, ggplot2, ggraph, igraph, inTrees, stringr, caret, ggpubr, ranger, xgboost, parallel, clustermq, utils, randomForest, tidyverse
RoxygenNote: 7.2.0
VignetteBuilder: knitr
Depends: 
    R (>= 2.10)
BugReports: https://github.com/aruaud/endoR/issues
URL: https://github.com/aruaud/endoR
Config/testthat/edition: 3