fuzzyclara

fuzzyclara: Efficient Medoid-based Clustering Algorithms for Large and Fuzzy Data - Published in JOSS (2025)

https://github.com/bauer-alex/fuzzyclara

Science Score: 93.0%

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Efficient medoid-based clustering algorithms for large and fuzzy data

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  • Stars: 3
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created almost 4 years ago · Last pushed 9 months ago
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README.md

fuzzyclara

R build status Codecov test coverage MIT license <!-- --> <!-- badges: end -->

Efficient and fuzzy clustering based on the CLARA algorithm

  • Authors: Maximilian Weigert, Alexander Bauer, Jana Gauss
  • Contributors: Theresa Kriecherbauer, Asmik Nalmpatian
  • Version: 1.0.1

Aim of this Package

The fuzzyclara package tackles two issues of cluster analysis applications. First, it includes routines for fuzzy clustering which avoid the common hard clustering assumption that each observation is a clear member of one sole cluster. Instead, membership probabilities indicate to which extent the characteristics of each observation are shaped by the characteristics of several 'typical' clusters. Second, the estimation of classical clustering algorithms is often only hardly or not at all feasible in large data situations with thousands of observations. Subsampling-based algorithms building on the CLARA algorithm are implemented to make the estimation feasible in such situations. Building on these two points, the 'fuzzyclara' package offers routines for all aspects of a cluster analysis, including the use of user-defined distance functions and diverse visualization techniques.

Documentation and Useful Materials

To get an overview of the functionalities of the package, check out the JOSS publication or the package vignette.

Installation

The most current version from GitHub can be installed via

``` r devtools::install_github("bauer-alex/fuzzyclara")

potential installation problems (specifically on MacOS) might be resolved

by previously specifically installing some dependency packages

install.packages(c("vegclust", "ggwordcloud", "ggpubr", "factoextra")) ```

How to Contribute

If you encounter problems with the package, find bugs or have suggestions for additional functionalities please open a GitHub issue. Alternatively, feel free to contact us directly via email.

Contributions (via pull requests or otherwise) are welcome. Please adhere to the Advanced R style guide when contributing code. Before you open a pull request or share your updates with us, please make sure that all unit tests pass without errors or warning messages. You can run the unit tests by calling

r devtools::test()

Owner

  • Name: Alexander Bauer
  • Login: bauer-alex
  • Kind: user

JOSS Publication

fuzzyclara: Efficient Medoid-based Clustering Algorithms for Large and Fuzzy Data
Published
June 02, 2025
Volume 10, Issue 110, Page 7887
Authors
Maximilian Weigert ORCID
Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Germany
Alexander Bauer ORCID
Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Germany
Jana Gauss ORCID
Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Germany
Asmik Nalmpatian ORCID
Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Germany
Editor
Kanishka B. Narayan ORCID
Tags
cluster analysis high-dimensional data fuzzy clustering

GitHub Events

Total
  • Release event: 1
  • Issues event: 2
  • Watch event: 1
  • Push event: 85
Last Year
  • Release event: 1
  • Issues event: 2
  • Watch event: 1
  • Push event: 85

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 23
  • Total pull requests: 0
  • Average time to close issues: 4 months
  • Average time to close pull requests: N/A
  • Total issue authors: 2
  • Total pull request authors: 0
  • Average comments per issue: 0.74
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: less than a minute
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
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  • ghost (13)
  • bauer-alex (9)
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Dependencies

DESCRIPTION cran
  • R >= 2.10 depends
  • Matrix * imports
  • checkmate * imports
  • cluster * imports
  • dplyr * imports
  • factoextra * imports
  • ggplot2 * imports
  • ggpubr * imports
  • ggwordcloud * imports
  • parallel * imports
  • proxy * imports
  • scales * imports
  • tibble * imports
  • tidyr * imports
  • tidyselect * imports
  • vegclust * imports
  • knitr * suggests
  • rmarkdown * suggests
  • shiny * suggests
  • testthat >= 3.0.0 suggests
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  • r-lib/actions/check-r-package v2 composite
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.github/workflows/pkgdown.yaml actions
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  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
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.github/workflows/test-coverage.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite