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randomForest (version 4.5-6)

Breiman and Cutler's random forests for classification and regression

Description

Classification and regression based on a forest of trees using random inputs.

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Version

Install

install.packages('randomForest')

Monthly Downloads

103,210

Version

4.5-6

License

GPL version 2 or later

Maintainer

Andy Liaw

Last Published

September 22nd, 2024

Functions in randomForest (4.5-6)

importance

Extract variable importance measure
rfImpute

Missing Value Imputations by randomForest
na.roughfix

Rough Imputation of Missing Values
getTree

Extract a single tree from a forest.
MDSplot

Multi-dimensional Scaling Plot of Proximity matrix from randomForest
predict.randomForest

predict method for random forest objects
combine

Combine Ensembles of Trees
margin

Margins of randomForest Classifier
classCenter

Prototypes of groups.
rfNews

Show the NEWS file
imports85

The Automobile Data
tuneRF

Tune randomForest for the optimal mtry parameter
varUsed

Variables used in a random forest
randomForest

Classification and Regression with Random Forest
varImpPlot

Variable Importance Plot
outlier

Compute outlying measures
partialPlot

Partial dependence plot
grow

Add trees to an ensemble
treesize

Size of trees in an ensemble
plot.randomForest

Plot method for randomForest objects