A Toolbox for Conditional Inference Trees and Random Forests

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Documentation for package ‘moreparty’ version 0.4

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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