https://github.com/gagolews/clustering-benchmarks

A framework for benchmarking clustering algorithms
https://github.com/gagolews/clustering-benchmarks

benchmark-suite benchmarking cluster cluster-analysis clustering clustering-algorithms clustering-benchmarks clustering-evaluation data data-science dataset datasets ground-truth machine-learning

Last synced: 7 days ago
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A framework for benchmarking clustering algorithms

• Host: GitHub
• URL: https://github.com/gagolews/clustering-benchmarks
• Owner: gagolews
• License: other
• Created: 2020-04-21T08:22:08.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2024-11-12T14:40:09.000Z (2 months ago)
• Last Synced: 2025-01-01T21:11:55.345Z (14 days ago)
• Topics: benchmark-suite, benchmarking, cluster, cluster-analysis, clustering, clustering-algorithms, clustering-benchmarks, clustering-evaluation, data, data-science, dataset, datasets, ground-truth, machine-learning
• Language: Python
• Homepage: http://clustering-benchmarks.gagolewski.com/
• Size: 193 MB
• Stars: 36
• Watchers: 4
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: CITATION.cff

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README

        


# [A Framework for Benchmarking Clustering Algorithms](https://clustering-benchmarks.gagolewski.com/)

Maintained/edited/authored by [Marek Gagolewski](https://www.gagolewski.com).

This project aims to:

* **aggregate, polish, and standardise the existing clustering benchmark

    batteries** referred to across the machine learning and data mining

    literature,

* introduce **new datasets** of different dimensionalities,

    sizes, and cluster types,

* propose a **consistent methodology** for evaluating clustering algorithms.

See  for a detailed description.

**How to cite**:

Gagolewski M., A framework for benchmarking clustering algorithms,

*SoftwareX* **20**, 2022, 101270, ,

DOI: [10.1016/j.softx.2022.101270](https://doi.org/10.1016/j.softx.2022.101270).