The R Journal: accepted article

This article will be copy edited and may be changed before publication.

clustMixType: User-Friendly Clustering of Mixed-Type Data in R PDF download
Gero Szepannek

Abstract Clustering algorithms are designed to identify groups in data where traditionally the emphasis in research has been on numeric data and in consequence most traditional algorithms are devoted to this kind of data. A gap has uprised from industrial praxis by the fact that in most business applications the variables are of both types: numeric and categorical. In recent past an increasing number of algorithms for clustering of mixed-type data has been proposed. Many of these are based on the idea of Huang’s k-prototypes algorithm. This paper describes the R package clustMixType which provides an implementation of this algorithm 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

CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

  author = {Gero Szepannek},
  title = {{clustMixType: User-Friendly Clustering of Mixed-Type Data in
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-048},
  url = {}