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 |
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