A Survey of Popular R Packages for Cluster Analysis

Autor/inn/en	Flynt, Abby; Dean, Nema
Titel	A Survey of Popular R Packages for Cluster Analysis
Quelle	In: Journal of Educational and Behavioral Statistics, 41 (2016) 2, S.205-225 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998616631743
Schlagwörter	Multivariate Analysis; Computer Software; Comparative Analysis; Programming Languages; Models + Suchen Sie Ihr Suchwort? Multivariate Analyse; Analogiemodell
Abstract	Cluster analysis is a set of statistical methods for discovering new group/class structure when exploring data sets. This article reviews the following popular libraries/commands in the R software language for applying different types of cluster analysis: from the stats library, the kmeans, and hclust functions; the mclust library; the poLCA library; and the clustMD library. The packages/functions cover a variety of cluster analysis methods for continuous data, categorical data, or a collection of the two. The contrasting methods in the different packages are briefly introduced, and basic usage of the functions is discussed. The use of the different methods is compared and contrasted and then illustrated on example data. In the discussion, links to information on other available libraries for different clustering methods and extensions beyond basic clustering methods are given. The code for the worked examples in Section 2 is available at http://www.stats.gla.ac.uk/~nd29c/Software/ClusterReviewCode.R (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01