This package contains a rule induction toolkit to generate readable and editable rules from data.
Project description
rulelearn (v0.1)
This package contains a rule induction toolkit to generate readable and editable rules from data. The code was originally released within the larger AIX 360 package and is provided and extended here separately with less dependencies.
It contains the following components:
- Boolean Decision Rules via Column Generation (Light Edition) (Dash et al., 2018)
- Generalized Linear Rule Models (Wei et al., 2019)
- Fast Effective Rule Induction (Ripper) (William W Cohen, 1995)
- Relational Rule Network (R2N) (Kusters et al., 2022)
- trxf - Technical Rule Interchange Format - Rule Set Interchange providing common evaluation tools and PMML export for rule sets.
Installation
pip install rulelearn
Acknowledgements
rulelearn is built with the help of several open source packages. All of these are listed in requirements.txt and include:
- scikit-learn https://scikit-learn.org/stable/about.html
License Information
Apache 2.0
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