# MultiCons
This python package provides an implementation of the MultiCons (Multiple Consensus)
algorithm.
MultiCons is a consensus clustering method that uses the frequent closed itemset mining
technique to find similarities in the base clustering solutions.
The implementation aims to follow the original description of the MultiCons method from
the references below.
## Installation
MultiCons is available on the Python Package Index (PyPI). It's installable using `pip`:
```bash
pip install multicons
```
## Documentation
To get started, check out some examples or look up the reference API, please visit our
[documentation page](https://sergiosim.github.io/multicons/).
## References
Atheer A. "A closed patterns-based approach to the consensus clustering problem".
Other [cs.OH]. Université Côte d’Azur, 2016. English. <NNT : 2016AZUR4111>. <tel-01478626>
Retrieved from [tel.archives-ouvertes.fr](https://tel.archives-ouvertes.fr/tel-01478626)
Atheer A., Pasquier N., Precioso F. "Using Closed Patterns to Solve the Consensus Clustering Problem".
International Journal of Software Engineering and Knowledge Engineering 2016 26:09n10, 1379-1397
Raw data
{
"_id": null,
"home_page": "https://github.com/SergioSim/multicons",
"name": "multicons",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.9",
"maintainer_email": null,
"keywords": "MultiCons, Multiple Consensuses, Consensus clustering",
"author": "SergioSim",
"author_email": "sergio.simonian@etu.univ-cotedazur.fr",
"download_url": "https://files.pythonhosted.org/packages/a4/12/fb97232270f1b3809fd475097eedd08c2081de754e27d90e2c445f9f65e5/multicons-0.3.0.tar.gz",
"platform": null,
"description": "# MultiCons\n\nThis python package provides an implementation of the MultiCons (Multiple Consensus)\nalgorithm.\n\nMultiCons is a consensus clustering method that uses the frequent closed itemset mining\ntechnique to find similarities in the base clustering solutions.\n\nThe implementation aims to follow the original description of the MultiCons method from\nthe references below.\n\n## Installation\n\nMultiCons is available on the Python Package Index (PyPI). It's installable using `pip`:\n\n```bash\npip install multicons\n```\n\n## Documentation\n\nTo get started, check out some examples or look up the reference API, please visit our\n[documentation page](https://sergiosim.github.io/multicons/).\n\n## References\n\nAtheer A. \"A closed patterns-based approach to the consensus clustering problem\".\nOther [cs.OH]. Universit\u00e9 C\u00f4te d\u2019Azur, 2016. English. <NNT : 2016AZUR4111>. <tel-01478626>\nRetrieved from [tel.archives-ouvertes.fr](https://tel.archives-ouvertes.fr/tel-01478626)\n\nAtheer A., Pasquier N., Precioso F. \"Using Closed Patterns to Solve the Consensus Clustering Problem\".\nInternational Journal of Software Engineering and Knowledge Engineering 2016 26:09n10, 1379-1397\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "MultiCons (Multiple Consensuses) algorithm",
"version": "0.3.0",
"project_urls": {
"Homepage": "https://github.com/SergioSim/multicons"
},
"split_keywords": [
"multicons",
" multiple consensuses",
" consensus clustering"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "00b158634eb1824affce52c77cd268a7aac2666dadf7628fbf29b5540dd357f0",
"md5": "e596ec7f7ee3e8deddf6a8cca1861db3",
"sha256": "9e5bf663d6f62ae041b2420d4fccb8838124beca1e282cea7a354dbdc23e0879"
},
"downloads": -1,
"filename": "multicons-0.3.0-py2.py3-none-any.whl",
"has_sig": false,
"md5_digest": "e596ec7f7ee3e8deddf6a8cca1861db3",
"packagetype": "bdist_wheel",
"python_version": "py2.py3",
"requires_python": ">=3.9",
"size": 11722,
"upload_time": "2024-05-09T17:54:36",
"upload_time_iso_8601": "2024-05-09T17:54:36.304162Z",
"url": "https://files.pythonhosted.org/packages/00/b1/58634eb1824affce52c77cd268a7aac2666dadf7628fbf29b5540dd357f0/multicons-0.3.0-py2.py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "a412fb97232270f1b3809fd475097eedd08c2081de754e27d90e2c445f9f65e5",
"md5": "01d79ca4689a922763502b89dbab86c2",
"sha256": "4fc164a64c8eda61e328e91d53da262013b8e9facf7d72655d5d5cee4467aa60"
},
"downloads": -1,
"filename": "multicons-0.3.0.tar.gz",
"has_sig": false,
"md5_digest": "01d79ca4689a922763502b89dbab86c2",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9",
"size": 14461,
"upload_time": "2024-05-09T17:54:38",
"upload_time_iso_8601": "2024-05-09T17:54:38.253385Z",
"url": "https://files.pythonhosted.org/packages/a4/12/fb97232270f1b3809fd475097eedd08c2081de754e27d90e2c445f9f65e5/multicons-0.3.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-05-09 17:54:38",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "SergioSim",
"github_project": "multicons",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"circle": true,
"lcname": "multicons"
}