pre: An R Package for Fitting Prediction Rule Ensembles

By Marjolein Fokkema. 2017

9 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Gérard Biau
2. Erwan Scornet
3. Clément Bénard
4. Sébastien Da Veiga
5. Houtao Deng
6. Stefan Wager
7. Emilio Carrizosa
8. Susan Athey

Citations in the corpus

• Interpreting tree ensembles with inTrees (2014, background): “, reduced decision nodes referred to as node harvest [28], rules generated from simplified predictive regions [22,23], single decision trees [3,4,34, 36], and linear models [14].”
• Interpretable Random Forests via Rule Extraction (2020, methodology): “We also use available R implementations pre (Fokkema, 2017, RuleFit) and nodeharvest (Meinshausen, 2015).”
• SIRUS: making random forests interpretable (2019, methodology): “, 2018), pre (Fokkema, 2017), nodeharvest (Meinshausen, 2015), and sbrl (Yang et al.”