文章基本信息

标题：Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R
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作者：Angelos Markos ; Alfonso Iodice D'Enza ; Michel van de Velden 等
期刊名称：Journal of Statistical Software
印刷版ISSN：1548-7660
电子版ISSN：1548-7660
出版年度：2019
卷号：91
期号：1
页码：1-24
DOI：10.18637/jss.v091.i10
出版社：University of California, Los Angeles
摘要：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.
关键词：dimension reduction; clustering; principal component analysis; multiple correspondence analysis; K-means.
其他关键词：dimension reduction;clustering;principal component analysis;multiple correspondence analysis;K-means