| 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. |
| Outliers | Computes outliers |
| Prototypes | Prototypes of groups |
| SurrogateTree | Surrogate tree for conditional inference random forests |
| titanic | Titanic dataset |