DESCRIPTION

Package: mrIML
Type: Package
Title: Multi Response Interpretable Machine Learning
Version: 2.0.0
Authors@R: c(
    person("Nick", "Fountain-Jones", , "nfountainjones@gmail.com", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0001-9248-8493")),
    person("Gustavo", "Machado", , "gmachad@ncsu.edu", role = c("aut"),
           comment = c(ORCID = "0000-0001-7552-6144")),
    person("Chris", "Kozakiewicz", role = "aut"),
    person("Nick", "Clark", role = "aut")
  )
Description: This package aims to enable users to build and interpret multivariate machine learning models harnessing the tidyverse (tidy model syntax in particular). This package builds off ideas from Gradient Forests (Ellis et al 2012), ecological genomic approaches (Fitzpatrick and Keller, 2014) and multi-response stacking algorithms (Xing et al 2019).
Depends: R (>= 3.5.0)
Imports:
    ape,
    breakDown,
    DALEX,
    ggtext,
    ggsci,
    imputeTS,
    pkgdown,
    tidymodels,
    randomForest,
    gbm,
    pacman,
    tidyverse,
    parallel,
    doParallel,
    viridis,
    janitor,
    hrbrthemes,
    vegan,
    flashlight,
    ggrepel,
    parsnip,
    rsample,
    workflows,
    stats,
    utils,
    ranger,
    future.apply,
    future,
    yaImpute,
    MetricsWeighted,
    dplyr,
    plyr,
    purrr,
    scales,
    tibble,
    tune,
    yardstick,
    MRFcov,
    finetune, 
    igraph,
    ggnetwork,
    network,
    gridExtra,
    xgboost,
    brulee,
    fastshap,
    tabnet,
    bonsai,
    cowplot,
    progress,
    hstats,
    geosphere
Suggests: knitr, rmarkdown
License: MIT + file LICENSE
LazyData: true    
VignetteBuilder: knitr, rmarkdown
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
URL: https://github.com/nfj1380/mrIML
BugReports: https://github.com/nfj1380/mrIML/issues
Config/testthat/edition: 3
Encoding: UTF-8