Name | rulelearn JSON |
Version |
0.1.2
JSON |
| download |
home_page | https://github.com/IBM/rulelearn |
Summary | This package contains a rule induction toolkit to generate readable and editable rules from data. |
upload_time | 2023-05-06 21:17:22 |
maintainer | |
docs_url | None |
author | Various |
requires_python | |
license | |
keywords |
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requirements |
No requirements were recorded.
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# 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](https://github.com/Trusted-AI/AIX360) 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](https://papers.nips.cc/paper/7716-boolean-decision-rules-via-column-generation))
- Generalized Linear Rule Models ([Wei et al., 2019](http://proceedings.mlr.press/v97/wei19a.html))
- Fast Effective Rule Induction (Ripper) ([William W Cohen, 1995](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.107.2612&rep=rep1&type=pdf))
- Relational Rule Network (R2N) ([Kusters et al., 2022](https://arxiv.org/abs/2201.06515))
- 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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