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: 2 months 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 (about 5 years ago)
- Default Branch: master
- Last Pushed: 2025-04-08T11:44:52.000Z (2 months ago)
- Last Synced: 2025-04-10T03:56:07.741Z (2 months 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: 194 MB
- Stars: 38
- Watchers: 3
- Forks: 6
- Open Issues: 1
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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 more details.
**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).