kamila: Methods for Clustering Mixed-Type Data

Implements methods for clustering mixed-type data, specifically combinations of continuous and nominal data. Special attention is paid to the often-overlooked problem of equitably balancing the contribution of the continuous and categorical variables. This package implements KAMILA clustering, a novel method for clustering mixed-type data in the spirit of k-means clustering. It does not require dummy coding of variables, and is efficient enough to scale to rather large data sets. Also implemented is Modha-Spangler clustering, which uses a brute-force strategy to maximize the cluster separation simultaneously in the continuous and categorical variables. For more information, see Foss, Markatou, Ray, & Heching (2016) <doi:10.1007/s10994-016-5575-7> and Foss & Markatou (2018) <doi:10.18637/jss.v083.i13>.

Package details

AuthorAlexander Foss [aut, cre], Marianthi Markatou [aut]
MaintainerAlexander Foss <[email protected]>
LicenseGPL-3 | file LICENSE
Version0.1.2
URL https://github.com/ahfoss/kamila
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("kamila")

Try the kamila package in your browser

Any scripts or data that you put into this service are public.

kamila documentation built on March 13, 2020, 9:08 a.m.