The R Journal: article published in 2018, volume 10:2

clustMixType: User-Friendly Clustering of Mixed-Type Data in R PDF download
Gero Szepannek , The R Journal (2018) 10:2, pages 200-208.

Abstract 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.

Received: 2017-10-30; online 2018-12-07, supplementary material, (1.1 Kb)
CRAN packages: gower, cluster, CluMix, flexclust, fpc, clustMD, kamila, clustMixType, klaR, wesanderson, clusteval
CRAN Task Views implied by cited CRAN packages: Cluster, Multivariate, Environmetrics, Graphics, MachineLearning, Robust


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