Nomclust 2.0: an R package for hierarchical clustering of objects characterized by nominal variables

Zdenek Sulc (), Jana Cibulkova and Hana Rezankova
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Zdenek Sulc: Prague University of Economics and Business
Jana Cibulkova: Prague University of Economics and Business
Hana Rezankova: Prague University of Economics and Business

Computational Statistics, 2022, vol. 37, issue 5, No 4, 2184 pages

Abstract: Abstract In this paper, we present the second generation of the nomclust R package, which we developed for the hierarchical clustering of data containing nominal variables (nominal data). The package completely covers the hierarchical clustering process, from dissimilarity matrix calculation, over the choice of a clustering method, to the evaluation of the final clusters. Through the whole clustering process, similarity measures, clustering methods, and evaluation criteria developed solely for nominal data are used, which makes this package unique. In the first part of the paper, the theoretical background of the methods used in the package is described. In the second part, the functionality of the package is demonstrated in several examples. The second generation of the package is completely rewritten to be more natural for the workflow of R users. It includes new similarity measures and evaluation criteria. We also added several graphical outputs and support for S3 generic functions. Finally, due to code optimizations, the calculation time of dissimilarity matrix calculation was substantially reduced.

Keywords: Categorical data; Similarity measures; Evaluation criteria; Agglomerative clustering (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00180-022-01209-4

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