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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.

modelenginemode
C5_rulesC5.0classification
cubist_rulesCubistregression
rule_fitxrfclassification
rule_fitxrfregression

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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Install

install.packages('rules')

Monthly Downloads

1,259

Version

1.0.2

License

MIT + file LICENSE

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Maintainer

Last Published

March 8th, 2023

Functions in rules (1.0.2)

rules-package

rules: Model Wrappers for Rule-Based Models
committees

Parameter functions for Cubist models
multi_predict._cubist

multi_predict() methods for rule-based models
tidy.C5.0

Turn C5.0 and rule-based models into tidy tibbles
c5_fit

Internal function wrappers
reexports

Objects exported from other packages