[R] RuleOpt: Optimization-Based Rule Learning for Classification

**Paper**: [https://arxiv.org/abs/2104.10751](https://arxiv.org/abs/2104.10751)

**Package:** [https://github.com/sametcopur/ruleopt](https://github.com/sametcopur/ruleopt)

**Documentation:** [https://ruleopt.readthedocs.io/](https://ruleopt.readthedocs.io/)

RuleOpt is an optimization-based rule learning algorithm designed for classification problems. Focusing on scalability and interpretability, RuleOpt utilizes linear programming for rule generation and extraction.

The Python library ruleopt is capable of extracting rules from ensemble models, and it also implements a novel rule generation scheme. The library ensures compatibility with existing machine learning pipelines, and it is especially efficient for tackling large-scale problems.

Here are a few highlights of ruleopt:

* **Efficient Rule …

algorithm classification ensemble extraction interpretability library linear machine machine learning machinelearning novel optimization pipelines programming python rules scalability