Skip to content

This code package implements Algorithm FRL and Algorithm softFRL described in the paper "An Optimization Approach to Learning Falling Rule Lists" by Chen and Rudin (AISTATS 2018).

Notifications You must be signed in to change notification settings

cfchen-duke/FRLOptimization

Repository files navigation

FRLOptimization

DESCRIPTION

This code package implements Algorithm FRL and Algorithm softFRL described in the paper "An Optimization Approach to Learning Falling Rule Lists" by Chen and Rudin (AISTATS 2018).

The supplementary material for the paper can be found in supplement.pdf.

REQUIREMENTS

This code requires Python 2.7, numpy, and fpgrowth from fim package (available at http://www.borgelt.net/pyfim.html).

RUN

See main.py for an example of how to use the code. To run main.py, type in a terminal:

$ python main.py

About

This code package implements Algorithm FRL and Algorithm softFRL described in the paper "An Optimization Approach to Learning Falling Rule Lists" by Chen and Rudin (AISTATS 2018).

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages