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>.
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") devtools::install_github("tidymodels/rules")
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
|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|
Last month downloads
|License||MIT + file LICENSE|
|Packaged||2020-05-09 16:48:31 UTC; max|
|Date/Publication||2020-05-20 15:00:02 UTC|
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