DESCRIPTION

Package: mikropml
Title: User-Friendly R Package for Supervised Machine Learning Pipelines
Version: 1.5.0.9000
Date: 2023-01-15
Authors@R: 
    c(person(given = "Begüm",
             family = "Topçuoğlu",
             role = "aut",
             email = "topcuoglu.begum@gmail.com",
             comment = c(ORCID = "0000-0003-3140-537X")),
      person(given = "Zena",
             family = "Lapp",
             role = "aut",
             email = "zenalapp@umich.edu",
             comment = c(ORCID = "0000-0003-4674-2176")),
      person(given = "Kelly",
             family = "Sovacool",
             role = c("aut", "cre"),
             email = "sovacool@umich.edu",
             comment = c(ORCID = "0000-0003-3283-829X")),
      person(given = "Evan",
             family = "Snitkin",
             role = "aut",
             comment = c(ORCID = "0000-0001-8409-278X")),
      person(given = "Jenna",
             family = "Wiens",
             role = "aut",
             comment = c(ORCID = "0000-0002-1057-7722")),
      person(given = "Patrick",
             family = "Schloss",
             role = "aut",
             email = "pschloss@umich.edu",
             comment = c(ORCID = "0000-0002-6935-4275")),
      person(given = "Nick",
             family = "Lesniak",
             role = "ctb",
             email = "nlesniak@umich.edu",
             comment = c(ORCID = "0000-0001-9359-5194")),
      person(given = "Courtney",
             family = "Armour",
             role = "ctb",
             email = "armourc@umich.edu",
             comment = c(ORCID = "0000-0002-5250-1224")),
      person(given = "Sarah",
             family = "Lucas",
             role = "ctb",
             email = "salucas@umich.edu",
             comment = c(ORCID = "0000-0003-1676-5801")))
Description: An interface to build machine learning models for
    classification and regression problems. 'mikropml' implements the ML
    pipeline described by Topçuoğlu et al. (2020)
    <doi:10.1128/mBio.00434-20> with reasonable default options for data
    preprocessing, hyperparameter tuning, cross-validation, testing, model
    evaluation, and interpretation steps.  See the website
    <https://www.schlosslab.org/mikropml/> for more information,
    documentation, and examples.
License: MIT + file LICENSE
URL: https://www.schlosslab.org/mikropml/,
    https://github.com/SchlossLab/mikropml
BugReports: https://github.com/SchlossLab/mikropml/issues
Depends:
    R (>= 4.1.0)
Imports:
    caret,
    dplyr,
    e1071,
    glmnet,
    kernlab,
    MLmetrics,
    randomForest,
    rlang,
    rpart,
    stats,
    utils,
    xgboost
Suggests:
    assertthat,
    doFuture,
    forcats,
    foreach,
    future,
    future.apply,
    furrr,
    ggplot2,
    knitr,
    progress,
    progressr,
    purrr,
    rmarkdown,
    rsample,
    testthat,
    tidyr
VignetteBuilder: 
    knitr
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Config/testthat/edition: 3