Methods for Joint Dimension Reduction and Clustering

A class of methods that combine dimension reduction and clustering of continuous or categorical data. For continuous data, the package contains implementations of factorial K-means (Vichi and Kiers 2001; ) and reduced K-means (De Soete and Carroll 1994; ); both methods that combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means (Hwang, Dillon and Takane 2006; ), i-FCB (Iodice D'Enza and Palumbo 2013, ) and Cluster Correspondence Analysis (van de Velden, Iodice D'Enza and Palumbo 2017; ), which combine multiple correspondence analysis with K-means.


Reference manual

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1.2.0 by Angelos Markos, 4 months ago

Browse source code at

Authors: Angelos Markos [aut, cre], Alfonso Iodice D'Enza [aut], Michel van de Velden [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports corpcor, GGally, fpc, cluster, dplyr, plyr, ggrepel, ca, stats

Depends on ggplot2, dummies, grid

See at CRAN