themis: Extra Recipes Steps for Dealing with Unbalanced Data

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>.

Version:	1.0.2
Depends:	R (≥ 3.6), recipes (≥ 1.0.4)
Imports:	gower, lifecycle (≥ 1.0.3), dplyr, generics (≥ 0.1.0), purrr, RANN, rlang, ROSE, tibble, withr, glue, hardhat, vctrs
Suggests:	covr, dials (≥ 1.2.0), ggplot2, modeldata, testthat (≥ 3.0.0)
Published:	2023-08-14
DOI:	10.32614/CRAN.package.themis
Author:	Emil Hvitfeldt [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer:	Emil Hvitfeldt <emil.hvitfeldt at posit.co>
BugReports:	https://github.com/tidymodels/themis/issues
License:	MIT + file LICENSE
URL:	https://github.com/tidymodels/themis, https://themis.tidymodels.org
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	themis results

Documentation:

Reference manual:

themis.pdf

Downloads:

Package source:	themis_1.0.2.tar.gz
Windows binaries:	r-devel: themis_1.0.2.zip, r-release: themis_1.0.2.zip, r-oldrel: themis_1.0.2.zip
macOS binaries:	r-release (arm64): themis_1.0.2.tgz, r-oldrel (arm64): themis_1.0.2.tgz, r-release (x86_64): themis_1.0.2.tgz, r-oldrel (x86_64): themis_1.0.2.tgz
Old sources:	themis archive

Reverse dependencies:

Reverse imports:	pheble
Reverse suggests:	caret, mlr3pipelines, orbital

Linking:

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