rules
Model Wrappers for Rule-Based Models
Bindings for additional models for use with the 'parsnip'
package. Models include prediction rule ensembles (Friedman and
Popescu, 2008)
rules 
Introduction
rules is a parsnip extension package with model definitions for rule-based models, including:
- cubist models that have discrete rule sets that contain linear models with an ensemble method similar to boosting
- classification rules where a ruleset is derived from an initial tree fit
- rule-fit models that begin with rules extracted from a tree ensemble which are then added to a regularized linear or logistic regression.
Installation
You can install the released version of rules from CRAN with:
install.packages("rules")
Install the development version from GitHub with:
# install.packages("pak")
pak::pak("tidymodels/rules")
Available Engines
The rules package provides engines for the models in the following table.
| model | engine | mode |
|---|---|---|
| C5_rules | C5.0 | classification |
| cubist_rules | Cubist | regression |
| rule_fit | xrf | classification |
| rule_fit | xrf | regression |
Contributing
This project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
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If you think you have encountered a bug, please submit an issue.
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