Skip to main content

FairCORELS, a modified version of CORELS to build fair and interpretable models

Project description

Welcome to FairCorels, a Python library for learning fair and interpretable models using the Certifiably Optimal RulE ListS (CORELS) algorithm!

FairCORELS uses Python, Numpy, GMP, and a C++ compiler. GMP (GNU Multiple Precision library) is not required, but it is highly recommended, as it improves performance. If it is not installed, CORELS will run slower.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for faircorels-demo, version 1.3
Filename, size & hash File type Python version Upload date
faircorels-demo-1.3.tar.gz (121.9 kB) View hashes Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page