semvec/pypi-packages huggingface dataset:
scikit-mine 1.0.0
Pattern mining in Python
License: new BSD

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Scikit-mine : pattern mining in Python

* **Descriptive analysis**, leading to **interpretable**, concise descriptions using the `Minimum Description Length Principle <https://en.wikipedia.org/wiki/Minimum_description_length>`_
* **Fast** Algorithms
* **Simple, extendable API**, inspired by scikit-learn_

.. _scikit-learn: https://scikit-learn.org/


Resources
---------

* Free software: BSD license
* GitHub: https://github.com/scikit-mine/scikit-mine
* Documentation: https://scikit-mine.github.io/scikit-mine/


Quickstart
----------


scikit-mine is a Python module for pattern mining built on top of
Pandas/Numpy/SciPy and is distributed under the 3-Clause BSD license.

It is currently maintained by a team of volunteers.

See examples in the tutorials; the notebooks are available here_. To execute the tutorials, you will have to install jupyter notebook or jupyterlab (https://jupyter.org/install)


.. _here: https://github.com/scikit-mine/scikit-mine/tree/master/docs/tutorials


Dependencies
------------

scikit-mine requires Python>=3.8,
and some extra dependencies

* scipy>=1.2.1
* pandas>=1.0.0
* pyroaring>=0.3.4
* joblib>=0.11.1
* sortedcontainers>=2.1.0
* dataclasses>=0.6
* networkx
* wget>=3.2
* scikit-learn
* graphviz
* matplotlib
* pydot


Development
-----------

This project is funded by the `INRIA center in Rennes, Brittany, France <https://www.inria.fr/fr/centre-inria-rennes-bretagne-atlantique>`_.

We welcome new contributors of all experience levels. 


Internal Contributors
---------------------

- Rémi Adon (https://github.com/remiadon)
- Luis Galárraga (https://github.com/lgalarra)
- Josie Signe (https://github.com/Darlysia)
- Esther Galbrun (https://github.com/nurblageij)
- Hermann Courteille (https://github.com/hermann74)
- Cyril Regan (https://github.com/cyril-data)
- Thomas Betton (https://github.com/thomasbtnfr)