rfVarImpOOB
Unbiased Variable Importance for Random Forests
Computes a novel variable importance for random forests: Impurity reduction importance scores for out-of-bag (OOB) data complementing the existing inbag Gini importance, see also doi:10.1080/03610926.2020.1764042. The Gini impurities for inbag and OOB data are combined in three different ways, after which the information gain is computed at each split. This gain is aggregated for each split variable in a tree and averaged across trees.
- Version1.0.3
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- rfVarImpOOB citation info
- Last release07/01/2022
Documentation
Team
Markus Loecher
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends1 package
- Imports6 packages
- Suggests2 packages