Pattern mining in Python
Project description
Scikit-mine : pattern mining in Python
Descriptive analysis, leading to interpretable, concise descriptions using the Minimum Description Length Principle
Fast Algorithms
Simple, extendable API, inspired by scikit-learn
Resources
Free software: BSD license
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)
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.
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)
