We present theRpackageclustrdwhich implements a class of methods that combinedimension reduction and clustering of continuous or categorical data. In particular, forcontinuous data, the package contains implementations of factorial K-means and reducedK-means; both methods combine principal component analysis with K-means clustering.For categorical data, the package provides MCA K-means, i-FCB and cluster correspon-dence analysis, which combine multiple correspondence analysis with K-means. Twoexamples on real datasets are provided to illustrate the usage of the main functions.
Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R
Iodice D'Enza, Alfonso;
In corso di stampa
Abstract
We present theRpackageclustrdwhich implements a class of methods that combinedimension reduction and clustering of continuous or categorical data. In particular, forcontinuous data, the package contains implementations of factorial K-means and reducedK-means; both methods combine principal component analysis with K-means clustering.For categorical data, the package provides MCA K-means, i-FCB and cluster correspon-dence analysis, which combine multiple correspondence analysis with K-means. Twoexamples on real datasets are provided to illustrate the usage of the main functions.File in questo prodotto:
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