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Silhouette

An R package for silhouette-based diagnostics in standard, soft, and multi-way clustering.

Silhouette diagnostics assess clustering quality using cohesion and separation of clusters. This package implements silhouette widths for various clustering setups, including support for soft membership probabilities and multi-way clustering structures.


Installation

You can install the released version of Silhouette from GitHub using:

# Install devtools if needed
if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")
}

# Install from GitHub
devtools::install_github("kskbhat/Silhouette")

Once accepted on CRAN, install via:

install.packages("Silhouette")

Usage

Usage of the main functions is demonstrated in the package examples and documentation.

For an intro, see the vignette A quick tour of Silhouette, which is available as

vignette("Silhouette")

You can access the vignette from the User Guide tab in the top navigation bar of the package’s website.


References

Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53–65. doi:10.1016/0377-0427(87)90125-7

Van der Laan, M., Pollard, K., & Bryan, J. (2003). A new partitioning around medoids algorithm. Journal of Statistical Computation and Simulation, 73(8), 575–584. doi:10.1080/0094965031000136012

Campello, R. J., & Hruschka, E. R. (2006). A fuzzy extension of the silhouette width criterion for cluster analysis. Fuzzy Sets and Systems, 157(21), 2858–2875. doi:10.1016/j.fss.2006.07.006

Schepers, J., Ceulemans, E., & Van Mechelen, I. (2008). Selecting among multi-mode partitioning models of different complexities: A comparison of four model selection criteria. Journal of Classification, 25(1), 67–85. doi:10.1007/s00357-008-9005-9

Kassambara, A., & Mundt, F. (2020). factoextra: Extract and Visualize the Results of Multivariate Data Analyses. R package version 1.0.7. doi:10.32614/CRAN.package.factoextra

Raymaekers, J., & Rousseeuw, P. J. (2022). Silhouettes and quasi residual plots for neural nets and tree-based classifiers. Journal of Computational and Graphical Statistics, 31(4), 1332–1343. doi:10.1080/10618600.2022.2050249

Bhat Kapu, S., & Kiruthika. (2024). Some density-based silhouette diagnostics for soft clustering algorithms. Communications in Statistics: Case Studies, Data Analysis and Applications, 10(3–4), 221–238. doi:10.1080/23737484.2024.2408534

Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., & Hornik, K. (2025). cluster: Cluster Analysis Basics and Extensions. R package version 2.1.8.1. doi:10.32614/CRAN.package.cluster

Bhat Kapu, S., & Kiruthika, C. (2025). Block Probabilistic Distance Clustering: A Unified Framework and Evaluation. PREPRINT (Version 1) available at Research Square. doi:10.21203/rs.3.rs-6973596/v1

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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