R: Innovative Complex Split Procedures in Random Forests Through Candidate Split Sampling

# Innovative Complex Split Procedures in Random Forests Through Candidate Split Sampling

## Documentation for package ‘diversityForest’ version 0.6.0

- DESCRIPTION file.
- Package NEWS.

## Help Pages

diversityForest-package | Diversity Forests
ctg | Data on automatic analysis of cardiotocograms
diversityForest | Diversity Forests
divfor | Construct a basic diversity forest prediction rule that uses univariable, binary splitting.
hars | Data on human activity recognition using smartphones
importance | Diversity Forest variable importance
importance.divfor | Diversity Forest variable importance
interactionfor | Construct an interaction forest prediction rule and calculate EIM values as described in Hornung & Boulesteix (2022).
multifor | Construct a random forest prediction rule and calculate class-focused and discriminatory variable importance scores.
plot.interactionfor | Plot method for 'interactionfor' objects
plot.multifor | Plot method for 'multifor' objects
plotEffects | Interaction forest plots: exploring interaction forest results through visualisation
plotMcl | Plots of the (estimated) within-class distributions of variables
plotPair | Plot of the (estimated) simultaneous influence of two variables
plotVar | Plot of the (estimated) dependency structure of a variable 'x' on a categorical variable 'y'
predict.divfor | Diversity Forest prediction
predict.interactionfor | Interaction Forest prediction
predict.multifor | Random forest prediction using a saved forest from 'multifor'
predictions | Diversity Forest predictions
predictions.divfor | Diversity Forest predictions
predictions.divfor.prediction | Diversity Forest predictions
stock | Data on stock prices of aerospace companies
tunedivfor | Optimization of the values of the tuning parameters 'nsplits' and 'proptry'
zoo | Data on biological species