A Framework for Benchmarking Clustering Algorithms
Maintained/edited/authored by Marek Gagolewski.
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 https://clustering-benchmarks.gagolewski.com/ for more details.
How to cite: Gagolewski M., A framework for benchmarking clustering algorithms, SoftwareX 20, 2022, 101270, https://clustering-benchmarks.gagolewski.com, DOI: 10.1016/j.softx.2022.101270.
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Release files for clustering-benchmarks 1.1.6
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| File | Size | Uploaded | Provenance | Actions |
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| clustering_benchmarks-1.1.6.tar.gz | 24.3 kB | Without provenance | Details for clustering_benchmarks-1.1.6.tar.gz |
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| clustering_benchmarks-1.1.6-py3-none-any.whl | Python 3 | none | any | Details for clustering_benchmarks-1.1.6-py3-none-any.whl |
Total release size: 53.2 kB
Release files / clustering_benchmarks-1.1.6.tar.gz
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Release files / clustering_benchmarks-1.1.6-py3-none-any.whl
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