tidyrules
Utilities to Retrieve Rulelists from Model Fits, Filter, Prune, Reorder and Predict on Unseen Data
Provides a framework to work with decision rules. Rules can be extracted from supported models, augmented with (custom) metrics using validation data, manipulated using standard dataframe operations, reordered and pruned based on a metric, predict on unseen (test) data. Utilities include; Creating a rulelist manually, Exporting a rulelist as a SQL case statement and so on. The package offers two classes; rulelist and ruleset based on dataframe.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.7 |
rolling linux/jammy R-4.5 | tidyrules_0.2.7.tar.gz |
618.5 KiB |
0.2.7 |
rolling linux/noble R-4.5 | tidyrules_0.2.7.tar.gz |
618.1 KiB |
0.2.7 |
rolling source/ R- | tidyrules_0.2.7.tar.gz |
453.5 KiB |
0.2.7 |
latest linux/jammy R-4.5 | tidyrules_0.2.7.tar.gz |
618.5 KiB |
0.2.7 |
latest linux/noble R-4.5 | tidyrules_0.2.7.tar.gz |
618.1 KiB |
0.2.7 |
latest source/ R- | tidyrules_0.2.7.tar.gz |
453.5 KiB |
0.2.7 |
2026-04-26 source/ R- | tidyrules_0.2.7.tar.gz |
453.5 KiB |
0.2.7 |
2026-04-23 source/ R- | tidyrules_0.2.7.tar.gz |
453.5 KiB |
0.2.7 |
2026-04-09 windows/windows R-4.5 | tidyrules_0.2.7.zip |
618.8 KiB |
0.2.7 |
2025-04-20 source/ R- | tidyrules_0.2.7.tar.gz |
453.5 KiB |
Dependencies (latest)
Imports
Suggests
- AmesHousing (>= 0.0.3)
- dplyr (>= 0.8)
- C50 (>= 0.1.2)
- Cubist (>= 0.2.2)
- rpart (>= 1.2.2)
- rpart.plot (>= 3.0.7)
- modeldata (>= 0.0.1)
- testthat (>= 2.0.1)
- MASS (>= 7.3.50)
- mlbench (>= 2.1.1)
- rmarkdown (>= 1.13)
- palmerpenguins (>= 0.1.1)