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.
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Notes
The datasets contained four numbers of variables (four, six, eight, ten), three ranges of categories (2–4, 2–6, 6–10), and the number of cases varied from 300 to 700. Each of the datasets contained four clusters with the middle between-cluster distance. All the combinations were five times replicated.
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This paper was supported by the Prague University of Economics and Business under grant IGA F4/44/2018.
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Sulc, Z., Cibulkova, J. & Rezankova, H. Nomclust 2.0: an R package for hierarchical clustering of objects characterized by nominal variables. Comput Stat 37, 2161–2184 (2022). https://doi.org/10.1007/s00180-022-01209-4
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DOI: https://doi.org/10.1007/s00180-022-01209-4