diversityForest: Innovative Complex Split Procedures in Random Forests Through
Candidate Split Sampling
Implementation of three methods based on the diversity forest (DF) algorithm
(Hornung, 2022, <doi:10.1007/s42979-021-00920-1>), a split-finding approach that
enables complex split procedures in random forests.
The package includes:
1. Interaction forests (IFs) (Hornung & Boulesteix, 2022, <doi:10.1016/j.csda.2022.107460>):
Model quantitative and qualitative interaction effects using bivariable splitting.
Come with the Effect Importance Measure (EIM), which can be used to identify variable
pairs that have well-interpretable quantitative and qualitative interaction effects
with high predictive relevance.
2. Two random forest-based variable importance measures (VIMs) for multi-class outcomes:
the class-focused VIM, which ranks covariates by their ability to distinguish individual
outcome classes from the others, and the discriminatory VIM, which measures overall
covariate influence irrespective of class-specific relevance.
3. The basic form of diversity forests that uses conventional univariable, binary
splitting (Hornung, 2022).
Except for the multi-class VIMs, all methods support categorical, metric, and survival
outcomes. The package includes visualization tools for interpreting the identified
covariate effects.
Built as a fork of the 'ranger' R package (main author: Marvin N. Wright), which
implements random forests using an efficient C++ implementation.
Version: |
0.6.0 |
Depends: |
R (≥ 3.5) |
Imports: |
Rcpp (≥ 0.11.2), Matrix, ggplot2, ggpubr, scales, nnet, sgeostat, rms, MapGAM, gam, rlang, grDevices, RColorBrewer, RcppEigen, survival, patchwork |
LinkingTo: |
Rcpp, RcppEigen |
Suggests: |
testthat, BOLTSSIRR |
Published: |
2025-05-05 |
DOI: |
10.32614/CRAN.package.diversityForest |
Author: |
Roman Hornung [aut, cre],
Marvin N. Wright [ctb, cph] |
Maintainer: |
Roman Hornung <hornung at ibe.med.uni-muenchen.de> |
License: |
GPL-3 |
NeedsCompilation: |
yes |
SystemRequirements: |
C++17 |
Additional_repositories: |
https://romanhornung.github.io/drat |
Materials: |
NEWS |
CRAN checks: |
diversityForest results |
Documentation:
Downloads:
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