rules v0.0.1


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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) <doi:10.1214/07-AOAS148>, C5.0 rules (Quinlan, 1992 ISBN: 1558602380), and Cubist (Kuhn and Johnson, 2013) <doi:10.1007/978-1-4614-6849-3>.



Lifecycle: experimental R build status Codecov test coverage CRAN status

rules is a "parsnip-adjacent" packages 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.


Th package is not yet on CRAN and can be installed via:

# install.packages("devtools")

Code of Conduct

Please note that the rules project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Functions in rules

Name Description
rule_fit General Interface for RuleFit Models
C5_rules General Interface for C5.0 Rule-Based Classification Models
committees Parameter functions for Cubist models
multi_predict._c5_rules multi_predict() methods for rule-based models
reexports Objects exported from other packages
mtry_prop Proportion of Randomly Selected Predictors
cubist_rules General Interface for Cubist Rule-Based Regression Models
c5_fit Internal function wrappers
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License MIT + file LICENSE
Encoding UTF-8
LazyData true
Language en-US
NeedsCompilation no
Packaged 2020-05-09 16:48:31 UTC; max
Repository CRAN
Date/Publication 2020-05-20 15:00:02 UTC

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