RF Variable Importance for Arbitrary Measures
Overview
Computes the random forest variable importance (VIMP) for the conditional inference random forest (cforest) of the 'party' package. Includes a function (varImp) that computes the VIMP for arbitrary measures from the 'measures' package. For calculating the VIMP regarding the measures accuracy and AUC two extra functions exist (varImpACC and varImpAUC).
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK12 OK2026-04-25
Show 1 earlier changeHide 1 earlier change
- NOTE11 OK, 3 NOTE2026-03-10
Documentation
- Help pages
- 4
- Examples that run
- 75%3 run in a plain check · 1 never run
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 25%
Downloads
Dependencies
Installing varImp adds 12 packages (7 with compiled code, 16 MB of source tarballs). Heaviest: TH.data 8.2 MB, sandwich 1.4 MB, coin 1.2 MB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 0.4Latest
- RR 4.0.0 released · 2020-04-24
- 0.3
- RR 3.6.0 released · 2019-04-26
- 0.22018-08-06 · diff ↗
- 0.12018-07-13
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-07-13
- Total releases
- 4 / 8 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.0.0
- Download size
- 8.2 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("varImp")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
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