fuzzy-c-means


Namefuzzy-c-means JSON
Version 1.7.0 PyPI version JSON
download
home_pagehttps://github.com/omadson/fuzzy-c-means
SummaryA simple python implementation of Fuzzy C-means algorithm.
upload_time2022-12-09 15:04:58
maintainer
docs_urlNone
authorMadson Dias
requires_python>=3.9,<4.0
licenseMIT
keywords machine-learning data-science fuzzy-c-means clustering
VCS
bugtrack_url
requirements click colorama joblib numpy pydantic tabulate tqdm typer typing-extensions
Travis-CI No Travis.
coveralls test coverage No coveralls. 
            # fuzzy-c-means

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**[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}
}
```

<!-- ### citations
 - [Gene-Based Clustering Algorithms: Comparison Between Denclue, Fuzzy-C, and BIRCH](https://doi.org/10.1177/1177932220909851)
 - [Analisis Data Log IDS Snort dengan Algoritma Clustering Fuzzy C-Means](https://doi.org/10.24843/MITE.2020.v19i01.P14)
 - [Comparative Analysis between the k-means and Fuzzy c-means Algorithms to Detect UDP Flood DDoS Attack on a SDN/NFV Environment](https://doi.org/10.5220/0010176201050112)
 - [Mixture-of-Experts Variational Autoencoder for Clustering and Generating from Similarity-Based Representations on Single Cell Data](https://arxiv.org/abs/1910.07763)
 - [Fuzzy Clustering: an Application to Distributional Reinforcement Learning](https://doi.org/10.34726/hss.2021.86783)
 - [Fuzzy Clustering with Similarity Queries](https://arxiv.org/pdf/2106.02212.pdf)
 - [Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variants](https://arxiv.org/abs/2110.09622)
 - [Unsupervised clustering-based spectral analysis of bio-dyed textile samples](http://urn.fi/urn:nbn:fi:uef-20211291) -->


## 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!

<!-- ## contributors
 - [Madson Dias](https://github.com/omadson)
 - [Dirk Nachbar](https://github.com/dirknbr)
 - [Alberth Florêncio](https://github.com/zealberth) -->

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

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Madson Dias
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