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rules

Introduction

rules is a “parsnip-adjacent” package with model definitions for different 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("devtools")
devtools::install_github("tidymodels/rules")

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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Version

Install

install.packages('rules')

Monthly Downloads

849

Version

0.1.1

License

MIT + file LICENSE

Issues

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Stars

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Maintainer

Max Kuhn

Last Published

January 16th, 2021

Functions in rules (0.1.1)

reexports

Objects exported from other packages
committees

Parameter functions for Cubist models
rule_fit

General Interface for RuleFit Models
cubist_rules

General Interface for Cubist Rule-Based Regression Models
tidy.cubist

Turn regression rule models into tidy tibbles
C5_rules

General Interface for C5.0 Rule-Based Classification Models
mtry_prop

Proportion of Randomly Selected Predictors
multi_predict._C5_rules

multi_predict() methods for rule-based models
c5_fit

Internal function wrappers