DESCRIPTION

Package: forester
Type: Package
Title: Quick and Simple Tools for Training and Testing of Tree-Based Models
Version: 1.6.1
Authors@R:
    c(person("Hubert", "Ruczyński", role = c("aut", "cre", "cph"), email = "hruczynski21@interia.pl"),
    person("Anna", "Kozak", role = c("aut", "ths"), email = "anna1993kozak@gmail.com"),
    person("Anna", "Cena", role = c("ths"), email = "anna.cena@pw.edu.pl"),
    person("Patryk", "Słowakiewicz", role = c("aut"), email = "slowakiewiczpatryk@outlook.com"),
    person("Adrianna", "Grudzień", role = c("aut"), email = "grudziena@outlook.com"),
    person("Przemysław", "Biecek", role = c("aut", "ths"), email = "przemyslaw.biecek@gmail.com"))
Description: The forester package is an open-source AutoML package implemented in R designed for
    training high-quality tree-based models on tabular data. It fully supports regression, binary
    classification, and multiclass classification tasks, and provides a limited support for
    the survival analysis task. A single line of code allows the use of unprocessed datasets, informs
    about potential issues concerning them, and handles feature engineering automatically.
    Moreover, hyperparameter tuning is performed by Bayesian optimization, which provides
    high-quality outcomes. The results are later served as a ranked list of models. Finally, the
    forester package offers a vast training report, including the ranked list, a comparison of
    trained models, and explanations for the best one.
License: GPL-3
Depends: 
    R (>= 3.5.0),
    patchwork
Imports:
    ranger,
    xgboost,
    lightgbm,
    ParBayesianOptimization,
    partykit,
    varhandle,
    mltools,
    data.table,
    splitTools,
    rcompanion,
    mice,
    rmarkdown,
    Boruta,
    ggplot2,
    ggrepel,
    pROC,
    stats,
    tibble,
    crayon,
    VIM
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.1
URL: https://github.com/ModelOriented/forester
BugReports: https://github.com/ModelOriented/forester/issues
Suggests: 
    testthat (>= 3.5.0),
    catboost,
    DALEX,
    ggradar,
    tinytex,
    knitr,
    rmcfs,
    varrank,
    arules,
    SurvMetrics,
    survival,
    randomForestSRC,
    sivs,
    foreach,
    doParallel,
    parallel
Config/testthat/edition: 3.5
VignetteBuilder:
    knitr