FairMclus: Clustering for Data with Sensitive Attribute (original) (raw)
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>".
| Version: | 2.2.1 |
|---|---|
| Imports: | dplyr, irr, rlist, tidyr, parallel, magrittr, cluster, base, data.table, foreach, doParallel |
| Published: | 2021-11-19 |
| DOI: | 10.32614/CRAN.package.FairMclus |
| Author: | Carlos Santos-Mangudo [aut, cre] |
| Maintainer: | Carlos Santos-Mangudo <carlossantos.csm at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | FairMclus results |
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