scikit-feature is an open-source (GNU General Public License v2.0) feature selection repository in Python developed by Data Mining and Machine Learning Lab at Arizona State University.

It serves as a platform for facilitating feature selection application, research and comparative study. It is designed to share widely used feature selection algorithms developed in the feature selection research, and offer convenience for researchers and practitioners to perform empirical evaluation in developing new feature selection algorithms.

This fork keeps the library working against modern versions of scikit-learn, based on the original scikit-feature project by Jundong Li, Kewei Cheng, and Suhang Wang of the DMML Lab@ASU.

Forked project information

• Project site - https://github.com/NoRaincheck/scikit-feature
• Documentation - https://noRaincheck.github.io/scikit-feature/ (build locally via make serve-docs)

Original scikit-feature project information

• Project site - https://github.com/jundongl/scikit-feature
• Documentation - http://featureselection.asu.edu/

Installation

From Sources

• Unpack the source package somewhere
• Run pip install -e . from the source distribution's top level folder

From pip

pip install skfeature-chappers

Running the Documentation Locally

The documentation is built with Material for MkDocs. To view documentation locally:

make serve-docs
# Then open http://localhost:8000 in your browser