Package: moreparty 0.4

moreparty: A Toolbox for Conditional Inference Trees and Random Forests

Additions to 'party' and 'partykit' packages : tools for the interpretation of forests (surrogate trees, prototypes, etc.), feature selection (see Gregorutti et al (2017) <arxiv:1310.5726>, Hapfelmeier and Ulm (2013) <doi:10.1016/j.csda.2012.09.020>, Altmann et al (2010) <doi:10.1093/bioinformatics/btq134>) and parallelized versions of conditional forest and variable importance functions. Also modules and a shiny app for conditional inference trees.

Authors:Nicolas Robette

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moreparty.pdf |moreparty.html✨
moreparty/json (API)
NEWS

# Install 'moreparty' in R:

install.packages('moreparty', repos = c('https://nicolas-robette.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nicolas-robette/moreparty/issues

Pkgdown site:https://nicolas-robette.github.io

Datasets:

titanic - Titanic dataset

On CRAN:

4.18 score 3 stars 8 scripts 283 downloads 25 exports 137 dependencies

Last updated 12 months agofrom:c2503d482b. Checks:6 OK, 3 NOTE. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 25 2025
R-4.5-win	NOTE	Mar 25 2025
R-4.5-mac	NOTE	Mar 25 2025
R-4.5-linux	NOTE	Mar 25 2025
R-4.4-win	OK	Mar 25 2025
R-4.4-mac	OK	Mar 25 2025
R-4.4-linux	OK	Mar 25 2025
R-4.3-win	OK	Mar 25 2025
R-4.3-mac	OK	Mar 25 2025

Exports:BivariateAssoc ctreeServer ctreeUI EasyTreeVarImp fastcforest fastvarImp fastvarImpAUC FeatureSelection GetAleData GetCtree GetInteractionStrength GetPartialData GetSplitStats ggForestEffects ggVarImp ictree NiceTreePlot NodesInfo NodeTreePlot Outliers PerfsBinClassif PerfsRegression Prototypes SurrogateTree TreeStab

Dependencies:backports base64enc bit bit64 bslib cachem cellranger checkmate class classInt cli clipr codetools coin colorspace commonmark cpp11 crayon crosstalk curl data.table datamods digest dplyr DT e1071 evaluate fansi farver fastmap fontawesome forcats foreach foreign Formula fs future future.apply generics ggplot2 globals glue gtable hardhat haven highr hms htmltools htmlwidgets httpuv iml inum isoband iterators jquerylib jsonlite KernSmooth knitr labeling later lattice lazyeval libcoin lifecycle listenv magrittr MASS Matrix matrixStats measures memoise Metrics mgcv mime modeltools multcomp munsell mvtnorm nlme parallelly party partykit pdp phosphoricons pillar pkgconfig plyr prettyunits progress promises proxy R.methodsS3 R.oo R.utils R6 rappdirs rclipboard RColorBrewer Rcpp reactable reactR readr readxl rematch rio rlang rmarkdown rpart sandwich sass scales shiny shinybusy shinyWidgets sourcetools sparsevctrs strucchange survival TH.data tibble tidyselect tinytex toastui tzdb utf8 varImp vctrs vip viridisLite vroom withr writexl xfun xtable yaml yardstick zoo

[en] An example of recursive partitioning with Titanic data

Nicolas Robette

Rendered fromTitanic_example.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2023-04-02
Started: 2020-06-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Bivariate association measures for supervised learning tasks.	BivariateAssoc
Shiny module to build and analyse conditional inference trees	ctree-module ctreeServer ctreeUI
Variable importance for conditional inference trees.	EasyTreeVarImp
Parallelized conditional inference random forest	fastcforest
Variable importance for conditional inference random forests	fastvarImp
Variable importance (with AUC performance measure) for conditional inference random forests	fastvarImpAUC
Feature selection for conditional random forests.	FeatureSelection
Accumulated Local Effects for a conditional random forest.	GetAleData
Gets a tree from a conditional random forest	GetCtree
Strength of interactions	GetInteractionStrength
Partial dependence for a conditional random forest.	GetPartialData
Permutation tests results for each split in a conditional tree.	GetSplitStats
Dot plot of covariates effects	ggForestEffects
Dot plot of variable importance	ggVarImp
An interactive app for conditional inference trees	ictree
Plots conditional inference trees.	NiceTreePlot
Informations about terminal nodes	NodesInfo
Plots the results of each node of a conditional inference tree	NodeTreePlot
Computes outliers	Outliers
Performance measures for binary classification tasks	PerfsBinClassif
Performance measures for regressions	PerfsRegression
Prototypes of groups	Prototypes
Surrogate tree for conditional inference random forests	SurrogateTree
Titanic dataset	titanic
Stability assessment of conditional inference trees	TreeStab