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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.
Getting started
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Package details |
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| Author | Srikanth Komala Sheshachala [aut, cre], Amith Kumar Ullur Raghavendra [aut] |
| Maintainer | Srikanth Komala Sheshachala <sri.teach@gmail.com> |
| License | GPL-3 |
| Version | 0.2.7 |
| URL | https://github.com/talegari/tidyrules https://talegari.github.io/tidyrules/ |
| Package repository | View on CRAN |
| Installation |
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