Abstract
Silhouette index is commonly used in cluster analysis for finding the optimal number of clusters, as well as for final clustering validation and evaluation as a synthetic indicator allowing to measure the general quality of clustering (relative compactness and separability of clusters—see Walesiak and Gatnar in Statystyczna analiza danych z wykorzystaniem programu R. PWN, Warszawa, p. 420, 2009). Its advantage is low computational complexity and simple interpretation rules. Recently, some proposals have appeared to use this index directly as basis of clustering algorithms. The paper is a tryout of the evaluation of such approach. In the paper examples, when the “mechanical” use of the silhouette index leads to the results that do not correspond to the actual structure of the classes are shown, the recommendations on the principles of the correct application of the index are presented.
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Appendices
Appendix 1: Source Code of Procedure of Finding Number of Cluster with Silhouette Index in R Language
Appendix 2: Source Code of Clustering Tree (RPCT) Algorithm Implementation in R Language
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Dudek, A. (2020). Silhouette Index as Clustering Evaluation Tool. In: Jajuga, K., Bat��g, J., Walesiak, M. (eds) Classification and Data Analysis. SKAD 2019. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-030-52348-0_2
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DOI: https://doi.org/10.1007/978-3-030-52348-0_2
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