scikit-mine 1.0.0

Pattern mining in Python

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

• 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)

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)