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MajKMeans  

k-Means Algorithm with a Majorization-Minimization Method
View on CRAN: Click here


Download and install MajKMeans package within the R console
Install from CRAN:
install.packages("MajKMeans")

Install from Github:
library("remotes")
install_github("cran/MajKMeans")

Install by package version:
library("remotes")
install_version("MajKMeans", "0.1.0")



Attach the package and use:
library("MajKMeans")
Maintained by
Sheikhi Ayyub
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-28
Latest Update: 2020-03-28
Description:
A hybrid of the K-means algorithm and a Majorization-Minimization method to introduce a robust clustering. The reference paper is: Julien Mairal, (2015) . The two most important functions in package 'MajKMeans' are cluster_km() and cluster_MajKm(). cluster_km() clusters data without Majorization-Minimization and cluster_MajKm() clusters data with Majorization-Minimization method. Both of these functions calculate the sum of squares (SS) of clustering.
How to cite:
Sheikhi Ayyub (2020). MajKMeans: k-Means Algorithm with a Majorization-Minimization Method. R package version 0.1.0, https://cran.r-project.org/web/packages/MajKMeans. Accessed 18 Sep. 2026.
Previous versions and publish date:
No previous versions
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Complete documentation for MajKMeans
Functions, R codes and Examples using the MajKMeans R package
Some associated functions: Euclid . clusters_MajKm . clusters_km . kmeans . 
Some associated R codes: kmeans.R .  Full MajKMeans package functions and examples
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