Package: diversityForest
Type: Package
Title: Innovative Complex Split Procedures in Random Forests Through
        Candidate Split Sampling
Version: 0.6.0
Date: 2025-05-03
Authors@R: c(person("Roman", "Hornung", role = c("aut", "cre"),
                     email = "hornung@ibe.med.uni-muenchen.de"),
              person("Marvin N.", "Wright", role = c("ctb", "cph")))
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>
Description: 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.
SystemRequirements: C++17
Encoding: UTF-8
License: GPL-3
Imports: Rcpp (>= 0.11.2), Matrix, ggplot2, ggpubr, scales, nnet,
        sgeostat, rms, MapGAM, gam, rlang, grDevices, RColorBrewer,
        RcppEigen, survival, patchwork
LinkingTo: Rcpp, RcppEigen
Depends: R (>= 3.5)
Suggests: testthat, BOLTSSIRR
Additional_repositories: https://romanhornung.github.io/drat
RoxygenNote: 7.3.2
NeedsCompilation: yes
Packaged: 2025-05-05 16:41:49 UTC; hornung
Author: Roman Hornung [aut, cre],
  Marvin N. Wright [ctb, cph]
Repository: CRAN
Date/Publication: 2025-05-05 17:00:03 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2025-12-29 20:43:22 UTC; windows
Archs: x64
