mahmoodalmansooei / clustering-data-v1

A Framework for Benchmarking Clustering Algorithms – Benchmark Suite Version 1

A Framework for Benchmarking Clustering Algorithms

Benchmark Suite Version 1 (with updates)

The aim of this project is to aggregate, polish, and standardise the existing clustering benchmark batteries referred to across the machine learning and data mining literature, and to introduce new datasets of different dimensionalities, sizes, and cluster types.

This repository is part of the Framework for Benchmarking Clustering Algorithms. It hosts the datasets from version 1 of the benchmark suite.

Refer to https://clustering-benchmarks.gagolewski.com for a detailed description, file format specification, example Python/R/MATLAB code, datasets explorer, and literature references.

Editor/Maintainer: Marek Gagolewski.

How to Cite: Please cite the following paper which describes the overall benchmarking methodology:

Gagolewski M., A framework for benchmarking clustering algorithms, SoftwareX 20, 2022, 101270, https://clustering-benchmarks.gagolewski.com, DOI: 10.1016/j.softx.2022.101270.

Additionally, mention the exact version of this benchmark suite (see Changelog below for version information):

Gagolewski M. et al. (Eds.), A benchmark suite for clustering algorithms: Version 1.1.0, 2022, https://github.com/gagolews/clustering-data-v1/releases/tag/v1.1.0, DOI: 10.5281/zenodo.7088171.

The datasets are provided solely for research purposes, unless stated otherwise. Please cite the literature references mentioned in the corresponding dataset description files in any publications that make use of these.

Changelog

The datasets and the reference labels included in this suite are versioned. This ensures reproducibility.

See https://github.com/gagolews/clustering-data-v1/releases/ for downloadable snapshots.

1.1.0 (2022-09-17)

• Each battery is now equipped with a README.txt file.

• New label vectors: wut/x2.labels1, wut/x3.labels1.

• Prettified (slightly) label vectors: graves/fuzzyx.labels[1-4], graves/parabolic.labels1.

• Deleted now redundant label vectors: graves/fuzzyx.labels5.

• The historical snapshot of this release is available at DOI: 10.5281/zenodo.7088171.

1.0.1 (2022-09-10)

• Updated dataset description files, e.g., fixed broken links.

• The code and the data repositories were separated; see https://github.com/gagolews/clustering-benchmarks and https://github.com/gagolews/clustering-data-v1.

• The project's homepage has been created. It is available at https://clustering-benchmarks.gagolewski.com.

• The historical snapshot of this release is available at DOI: 10.5281/zenodo.7066690.

1.0.0 (2020-05-08)

• Datasets in the 1st (v1.0.0) version of the benchmark battery are now frozen.

• The historical snapshot of this release is available at DOI: 10.5281/zenodo.3815066.

0.0.0 (2015-12-29)

• Version 0 of the benchmark suite consists of the datasets studied in: Gagolewski M., Bartoszuk M., Cena A., Genie: A new, fast, and outlier-resistant hierarchical clustering algorithm, Information Sciences 363, 2016, pp. 8–23, DOI: 10.1016/j.ins.2016.05.003. The datasets have been archived at https://github.com/gagolews/clustering-data-v0.

See Also

https://clustering-benchmarks.gagolewski.com gives a detailed description of the whole framework for benchmarking clustering algorithms.

It also mentions where to find raw and aggregated results generated by many clustering methods when run on the datasets from this repository.