We present the R package clustrd which implements a class of methods that combine dimension reduction and clustering of continuous or categorical data. In particular, for continuous data, the package contains implementations of factorial K-means and reduced K-means; both methods combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means, i-FCB and cluster correspondence analysis, which combine multiple correspondence analysis with K-means. Two examples on real datasets are provided to illustrate the usage of the main functions.

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Keywords dimension reduction, clustering, principal component analysis, multiple correspondence analysis, K-means.
Persistent URL hdl.handle.net/1765/112735
Journal Journal of Statistical Software (Online)
Citation
Markos, Angelos, Iodice D'Enza, Alfonzo, & van de Velden, M. (2018). Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R. Journal of Statistical Software (Online). Retrieved from http://hdl.handle.net/1765/112735