Function reference • randomForest

All functions
`MDSplot()`	Multi-dimensional Scaling Plot of Proximity matrix from randomForest
`classCenter()`	Prototypes of groups.
`combine()`	Combine Ensembles of Trees
`getTree()`	Extract a single tree from a forest.
`grow(<randomForest>)`	Add trees to an ensemble
`importance(<randomForest>)`	Extract variable importance measure
`imports85`	The Automobile Data
`margin(<randomForest>)` `margin(<default>)` `plot(<margin>)`	Margins of randomForest Classifier
`na.roughfix()`	Rough Imputation of Missing Values
`outlier(<default>)` `outlier(<randomForest>)`	Compute outlying measures
`partialPlot(<randomForest>)`	Partial dependence plot
`plot(<randomForest>)`	Plot method for randomForest objects
`predict(<randomForest>)`	predict method for random forest objects
`randomForest(<formula>)` `randomForest(<default>)` `print(<randomForest>)`	Classification and Regression with Random Forest
`rfImpute(<default>)` `rfImpute(<formula>)`	Missing Value Imputations by randomForest
`rfNews()`	Show the NEWS file
`rfcv()`	Random Forest Cross-Valdidation for feature selection
`treesize()`	Size of trees in an ensemble
`tuneRF()`	Tune randomForest for the optimal mtry parameter
`varImpPlot()`	Variable Importance Plot
`varUsed()`	Variables used in a random forest

Reference