scikit-mine
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scikit-mine : pattern mining in Python
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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 benefitted from fundings from the INRIA center in Rennes, Brittany, France <https://www.inria.fr/fr/centre-inria-rennes-bretagne-atlantique>, as well as from the CNRS PNRIA Programme <https://www.ins2i.cnrs.fr/fr/reseau-des-ingenieurs-cnrs-du-programme-national-de-recherche-en-intelligence-artificielle-pnria>.
We welcome new contributors of all experience levels.
Internal Contributors
- Rémi Adon (https://github.com/remiadon)
- Hermann Courteille (https://github.com/hermann74)
- Cyril Regan (https://github.com/cyril-data)
- Thomas Betton (https://github.com/thomasbtnfr)
- Esther Galbrun (https://github.com/nurblageij)
- Peggy Cellier (https://github.com/PeggyCellier)
- Alexandre Termier (https://github.com/alexandre-termier)
- Luis Galárraga (https://github.com/lgalarra)
- Josie Signe (https://github.com/Darlysia)
- Francesco Bariatti (https://github.com/fbariatti)
- Mensah-David Assigbi (https://github.com/davidassigbi)
- Arnauld-Cyriaque Djedjemel (https://github.com/Ariaque)