Package: FairMclus 2.2.1
Carlos Santos-Mangudo
FairMclus: Clustering for Data with Sensitive Attribute
Clustering for categorical and mixed-type of data, to preventing classification biases due to race, gender or others sensitive attributes. This algorithm is an extension of the methodology proposed by "Santos & Heras (2020) <doi:10.28945/4643>".
Authors:
FairMclus_2.2.1.tar.gz
FairMclus_2.2.1.tar.gz(r-4.5-noble)FairMclus_2.2.1.tar.gz(r-4.4-noble)
FairMclus_2.2.1.tgz(r-4.4-emscripten)FairMclus_2.2.1.tgz(r-4.3-emscripten)
FairMclus.pdf |FairMclus.html✨
FairMclus/json (API)
| # Install 'FairMclus' in R: |
| install.packages('FairMclus', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:8e7b538a28. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 07 2024 |
| R-4.5-linux | NOTE | Dec 07 2024 |
Exports:FairMclus
Dependencies:cliclustercodetoolscpp11data.tabledoParalleldplyrfansiforeachgenericsglueirriteratorsjsonlitelifecyclelpSolvemagrittrpillarpkgconfigpurrrR6rlangrliststringistringrtibbletidyrtidyselectutf8vctrswithrXMLyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| FairMclus Clustering for Data with Sensitive Attribute | FairMclus |