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 data sets are provided to illustrate the usage of the main functions.

Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R / Markos, Angelos; IODICE D'ENZA, Alfonso; van de Velden, Michel. - In: JOURNAL OF STATISTICAL SOFTWARE. - ISSN 1548-7660. - 91:10(2019), pp. 1-24. [10.18637/jss.v091.i10]

Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R

Iodice D'Enza Alfonso;
2019

Abstract

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 data sets are provided to illustrate the usage of the main functions.
2019
Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R / Markos, Angelos; IODICE D'ENZA, Alfonso; van de Velden, Michel. - In: JOURNAL OF STATISTICAL SOFTWARE. - ISSN 1548-7660. - 91:10(2019), pp. 1-24. [10.18637/jss.v091.i10]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/773186
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