silhouette

Silhouette-Based Diagnostics for Standard, Soft, and Multi-Way Clustering

https://github.com/kskbhat/silhouette

Science Score: 39.0%

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Low similarity (12.0%) to scientific vocabulary

Keywords

classification cluster-analysis clustering-algorithm membership-probability proximity-measure silhouette

Last synced: 6 months ago · JSON representation

Repository

Silhouette-Based Diagnostics for Standard, Soft, and Multi-Way Clustering

Basic Info

Host: GitHub
Owner: kskbhat
License: gpl-2.0
Language: R
Default Branch: main
Homepage: https://kskbhat.github.io/Silhouette/
Size: 13.5 MB

Statistics

Stars: 2
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 9

Topics

classification cluster-analysis clustering-algorithm membership-probability proximity-measure silhouette

Created 11 months ago · Last pushed 6 months ago

Metadata Files

Readme Changelog License

Silhouette

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

Quantifies clustering quality by measuring both cohesion within clusters and separation between clusters. Implements advanced silhouette width computations for diverse clustering structures, including: simplified silhouette by Van der Laan et al. (2003), Probability of Alternative Cluster normalization methods by Raymaekers & Rousseeuw (2022), fuzzy clustering and silhouette diagnostics using membership probabilities by Campello & Hruschka (2006), Menardi (20011) and Bhat & Kiruthika (2024), and multi-way clustering extensions such as block and tensor clustering by Schepers et al. (2008) and Bhat & Kiruthika (2025). Provides tools for computation and visualization based on Rousseeuw (1987) to support robust and reproducible cluster diagnostics across standard, soft, and multi-way clustering settings.

Note: This package does not use the classical Rousseeuw (1987) calculation directly.

✅ Why This Package?

Unified & consistent: Offers one coherent interface for crisp, soft, and multi-way clustering silhouette diagnostics.
Flexible: Works with distance matrices, clustering outputs, or soft membership probabilities.
Advanced: Implements newer normalization methods (PAC, db), handles soft clustering, and supports mode-wise silhouette aggregation.
Visualization: Plot functions produce clear, customizable silhouette plots compatible with many clustering outputs and existing silhouette outputs from factoextra, cluster and drclust R packages.
Comparability: Summaries and plots make it easy to compare clustering algorithms or tune the number of clusters.
Interoperable: All Silhouette class functions works with any clustering output that provides a proximity or membership probability matrix. Users can also supply a proximity matrix and a clustering function—including S3 or S4 methods—to let Silhouette class perform clustering and compute silhouettes internally in one step.

Installation

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

``` r

Install devtools if needed

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

Install from GitHub

devtools::install_github("kskbhat/Silhouette") ```

From CRAN, install via:

r install.packages("Silhouette")

Usage

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

For an intro, see the vignette Silhouette, which is available as

r vignette("Silhouette")

You can access the vignette from the Get started tab in the top navigation bar of the package's website.

Report a Bug or Request a Feature

If you encounter a bug or have an idea for a new feature in the Silhouette package, please let us know by opening an issue on GitHub:

Create an issue on GitHub
For bugs: include a minimal reproducible example, describe the expected vs. actual behavior, and mention your R and package versions
For feature requests: clearly describe the proposed feature, its purpose, and how it would benefit users

Your feedback and suggestions are valuable and help improve the package.

Owner

Login: kskbhat
Kind: user

Repositories: 1
Profile: https://github.com/kskbhat

GitHub Events

Total

Release event: 8
Watch event: 3
Delete event: 6
Issue comment event: 1
Public event: 1
Push event: 105
Pull request event: 2
Create event: 7

Last Year

Release event: 8
Watch event: 3
Delete event: 6
Issue comment event: 1
Public event: 1
Push event: 105
Pull request event: 2
Create event: 7

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 0
Total pull requests: 1
Average time to close issues: N/A
Average time to close pull requests: 13 minutes
Total issue authors: 0
Total pull request authors: 1
Average comments per issue: 0
Average comments per pull request: 0.0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 1
Average time to close issues: N/A
Average time to close pull requests: 13 minutes
Issue authors: 0
Pull request authors: 1
Average comments per issue: 0
Average comments per pull request: 0.0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

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Packages

Total packages: 1
Total downloads:
- cran 243 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 1
Total maintainers: 1

cran.r-project.org: Silhouette

Proximity Measure Based Diagnostics for Standard, Soft, and Multi-Way Clustering

Homepage: https://kskbhat.github.io/Silhouette/
Documentation: http://cran.r-project.org/web/packages/Silhouette/Silhouette.pdf
License: GPL-2
Latest release: 0.9.4
published 7 months ago

Versions: 1
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 243 Last month

Rankings

Dependent packages count: 25.7%

Dependent repos count: 31.7%

Average: 47.7%

Downloads: 85.6%

Maintainers (1)

skbhat.in@gmail.com