Welcome to scikit-mine’s documentation!¶
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 benefitted from fundings from the INRIA center in Rennes, Brittany, France, as well as from the CNRS PNRIA Programme.
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)
Installation
API Reference