https://github.com/omadson/fuzzy-c-means

A simple python implementation of Fuzzy C-means algorithm.
https://github.com/omadson/fuzzy-c-means

clustering clustering-algorithm clustering-methods clusterization fuzzy fuzzy-clustering fuzzy-cmeans-clustering hacktoberfest

Last synced: about 2 months ago
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A simple python implementation of Fuzzy C-means algorithm.

• Host: GitHub
• URL: https://github.com/omadson/fuzzy-c-means
• Owner: omadson
• License: mit
• Created: 2019-05-13T16:29:01.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2024-07-15T19:24:40.000Z (11 months ago)
• Last Synced: 2025-03-28T14:11:25.343Z (2 months ago)
• Topics: clustering, clustering-algorithm, clustering-methods, clusterization, fuzzy, fuzzy-clustering, fuzzy-cmeans-clustering, hacktoberfest
• Language: Python
• Homepage: https://fuzzy-c-means.rtfd.io
• Size: 7.64 MB
• Stars: 182
• Watchers: 2
• Forks: 45
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

        
# fuzzy-c-means

![GitHub](https://img.shields.io/github/license/omadson/fuzzy-c-means.svg)

[![PyPI](https://img.shields.io/pypi/v/fuzzy-c-means.svg)](http://pypi.org/project/fuzzy-c-means/)

[![Documentation Status](https://readthedocs.org/projects/fuzzy-c-means/badge/?version=latest)](https://fuzzy-c-means.readthedocs.io/en/latest/?badge=latest)

[![GitHub last commit](https://img.shields.io/github/last-commit/omadson/fuzzy-c-means.svg)](https://github.com/omadson/fuzzy-c-means/commit/master)

[![Downloads](https://pepy.tech/badge/fuzzy-c-means)](https://pepy.tech/project/fuzzy-c-means)

[![DOI](https://zenodo.org/badge/186457481.svg)](https://zenodo.org/badge/latestdoi/186457481)

**[Documentation](https://fuzzy-c-means.readthedocs.io/)** | **[Changelog](https://fuzzy-c-means.readthedocs.io/en/latest/CHANGELOG/)** | **[Citation](https://fuzzy-c-means.readthedocs.io/en/latest/citation/)**

`fuzzy-c-means` is a Python module implementing the [Fuzzy C-means][1] clustering algorithm.

## installation

the `fuzzy-c-means` package is available in [PyPI](https://pypi.org/project/fuzzy-c-means/). to install, simply type the following command:

```

pip install fuzzy-c-means

```

## citation

if you use `fuzzy-c-means` package in your paper, please cite it in your publication.

```

@software{dias2019fuzzy,

  author       = {Madson Luiz Dantas Dias},

  title        = {fuzzy-c-means: An implementation of Fuzzy $C$-means clustering algorithm.},

  month        = may,

  year         = 2019,

  publisher    = {Zenodo},

  doi          = {10.5281/zenodo.3066222},

  url          = {https://git.io/fuzzy-c-means}

}

```

## contributing and support

this project is open for contributions. here are some of the ways for you to contribute:

 - bug reports/fix

 - features requests

 - use-case demonstrations

please open an [issue](https://github.com/omadson/fuzzy-c-means/issues) with enough information for us to reproduce your problem. A [minimal, reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) would be very helpful.

to make a contribution, just fork this repository, push the changes in your fork, open up an issue, and make a pull request!

[1]: https://doi.org/10.1016/0098-3004(84)90020-7

[2]: http://scikit-learn.org/