DESCRIPTION

Package: themis
Title: Extra Recipes Steps for Dealing with Unbalanced Data
Version: 1.0.3.9000
Authors@R: c(
    person("Emil", "Hvitfeldt", , "emil.hvitfeldt@posit.co", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-0679-1945")),
    person(given = "Posit Software, PBC", role = c("cph", "fnd"))
  )
Description: A dataset with an uneven number of cases in each class is
    said to be unbalanced. Many models produce a subpar performance on
    unbalanced datasets. A dataset can be balanced by increasing the
    number of minority cases using SMOTE 2011 <doi:10.48550/arXiv.1106.1813>,
    BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008
    <https://ieeexplore.ieee.org/document/4633969>. Or by decreasing the
    number of majority cases using NearMiss 2003
    <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek
    link removal 1976 <https://ieeexplore.ieee.org/document/4309452>.
License: MIT + file LICENSE
URL: https://github.com/tidymodels/themis, https://themis.tidymodels.org
BugReports: https://github.com/tidymodels/themis/issues
Depends: 
    R (>= 3.6),
    recipes (>= 1.1.0)
Imports:
    cli,
    gower,
    lifecycle (>= 1.0.3),
    dplyr,
    generics (>= 0.1.0),
    purrr,
    RANN,
    rlang (>= 1.1.0),
    ROSE,
    tibble,
    withr,
    glue,
    hardhat,
    vctrs
Suggests: 
    covr,
    dials (>= 1.2.0),
    ggplot2,
    modeldata,
    testthat (>= 3.0.0)
Config/Needs/website: tidyverse/tidytemplate
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2