clustMixType: User-Friendly Clustering of Mixed-Type Data in R

Clustering algorithms are designed to identify groups in data where the traditional emphasis has been on numeric data. In consequence, many existing algorithms are devoted to this kind of data even though a combination of numeric and categorical data is more common in most business applications. Recently, new algorithms for clustering mixed-type data have been proposed based on Huang’s k-prototypes algorithm. This paper describes the R package clustMixType which provides an implementation of k-prototypes in R.

Gero Szepannek
2018-12-07

Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2018-048.zip

CRAN packages used

gower, cluster, CluMix, flexclust, fpc, clustMD, kamila, clustMixType, klaR, wesanderson, clusteval

CRAN Task Views implied by cited packages

Cluster, Multivariate, Environmetrics, Graphics, MachineLearning, Robust

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

Citation

For attribution, please cite this work as

Szepannek, "clustMixType: User-Friendly Clustering of Mixed-Type Data in R", The R Journal, 2018

BibTeX citation

@article{RJ-2018-048,
  author = {Szepannek, Gero},
  title = {clustMixType: User-Friendly Clustering of Mixed-Type Data in R},
  journal = {The R Journal},
  year = {2018},
  note = {https://doi.org/10.32614/RJ-2018-048},
  doi = {10.32614/RJ-2018-048},
  volume = {10},
  issue = {2},
  issn = {2073-4859},
  pages = {200-208}
}