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ClusterR  

Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ClusterR", "1.3.3")



Attach the package and use:
library("ClusterR")
Maintained by
Lampros Mouselimis
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-09-06
Latest Update: 2023-04-29
Description:
Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to speed up the computationally intensive parts of the functions. For more information, see (i) "Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, ; (ii) "Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, ; (iii) "Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, ; (iv) "Clustering by Passing Messages Between Data Points" by Brendan J. Frey and Delbert Dueck, Science 16 Feb 2007: Vol. 315, Issue 5814, pp. 972-976, .
How to cite:
Lampros Mouselimis (2016). ClusterR: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering. R package version 1.3.3, https://cran.r-project.org/web/packages/ClusterR. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0.0 (2016-09-06 15:59), 1.0.1 (2016-09-09 10:13), 1.0.3 (2016-10-08 22:25), 1.0.4 (2017-02-02 17:38), 1.0.5 (2017-02-11 10:26), 1.0.6 (2017-08-03 17:15), 1.0.7 (2017-10-14 00:14), 1.0.8 (2017-10-28 15:59), 1.0.9 (2017-11-30 14:00), 1.1.0 (2018-01-17 19:02), 1.1.1 (2018-02-26 18:17), 1.1.2 (2018-05-04 00:41), 1.1.3 (2018-07-21 23:00), 1.1.4 (2018-08-22 18:10), 1.1.5 (2018-10-05 12:12), 1.1.6 (2018-11-08 17:30), 1.1.7 (2018-12-10 01:00), 1.1.8 (2019-01-11 13:40), 1.1.9 (2019-04-14 08:42), 1.2.0 (2019-07-18 08:35), 1.2.1 (2019-11-29 20:50), 1.2.2 (2020-05-12 11:10), 1.2.3 (2021-05-03 20:20), 1.2.4 (2021-05-04 07:30), 1.2.5 (2021-05-21 08:40), 1.2.6 (2022-01-28 00:40), 1.2.7 (2022-09-21 07:00), 1.2.8 (2022-12-03 09:32), 1.2.9 (2022-12-13 08:50), 1.3.0 (2023-01-21 10:40), 1.3.1 (2023-04-29 21:00), 1.3.2 (2023-12-04 19:00)
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