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clustrd (version 1.2.0)

Methods for Joint Dimension Reduction and Clustering

Description

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.

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Version

Install

install.packages('clustrd')

Monthly Downloads

475

Version

1.2.0

License

GPL (>= 2)

Maintainer

Angelos Markos

Last Published

May 29th, 2017

Functions in clustrd (1.2.0)

plot.cluspca

Plotting function for cluspca() output.
tuneclus

Cluster quality assessment for a range of clusters and dimensions.
clusmca

Joint dimension reduction and clustering of categorical data.
cluspca

Joint dimension reduction and clustering of continuous data.
cmc

Contraceptive Choice in Indonesia
hsq

Humor Styles
macro

Economic Indicators of 20 OECD countries for 1999
plot.clusmca

Plotting function for clusmca() output.
underwear

South Korean Underwear