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randomForest (version 4.7-1.2)

Breiman and Cutlers Random Forests for Classification and Regression

Description

Classification and regression based on a forest of trees using random inputs, based on Breiman (2001) .

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Version

Install

install.packages('randomForest')

Monthly Downloads

90,696

Version

4.7-1.2

License

GPL (>= 2)

Maintainer

Last Published

September 22nd, 2024

Functions in randomForest (4.7-1.2)

plot.randomForest

Plot method for randomForest objects
randomForest

Classification and Regression with Random Forest
varImpPlot

Variable Importance Plot
varUsed

Variables used in a random forest
combine

Combine Ensembles of Trees
margin

Margins of randomForest Classifier
outlier

Compute outlying measures
na.roughfix

Rough Imputation of Missing Values
MDSplot

Multi-dimensional Scaling Plot of Proximity matrix from randomForest
imports85

The Automobile Data
grow

Add trees to an ensemble
classCenter

Prototypes of groups.
getTree

Extract a single tree from a forest.
partialPlot

Partial dependence plot
importance

Extract variable importance measure
predict.randomForest

predict method for random forest objects
tuneRF

Tune randomForest for the optimal mtry parameter
rfImpute

Missing Value Imputations by randomForest
rfcv

Random Forest Cross-Valdidation for feature selection
treesize

Size of trees in an ensemble
rfNews

Show the NEWS file