# A Toolbox for Conditional Inference Trees and Random Forests

## 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