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randomForest (version 4.5-28)
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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Install
install.packages('randomForest')
Monthly Downloads
93,657
Version
4.5-28
License
GPL version 2 or later
Maintainer
Andy Liaw
Last Published
September 22nd, 2024
Functions in randomForest (4.5-28)
Search all functions
na.roughfix
Rough Imputation of Missing Values
rfNews
Show the NEWS file
varImpPlot
Variable Importance Plot
varUsed
Variables used in a random forest
treesize
Size of trees in an ensemble
plot.randomForest
Plot method for randomForest objects
outlier
Compute outlying measures
grow
Add trees to an ensemble
imports85
The Automobile Data
classCenter
Prototypes of groups.
importance
Extract variable importance measure
getTree
Extract a single tree from a forest.
predict.randomForest
predict method for random forest objects
rfImpute
Missing Value Imputations by randomForest
tuneRF
Tune randomForest for the optimal mtry parameter
margin
Margins of randomForest Classifier
randomForest
Classification and Regression with Random Forest
partialPlot
Partial dependence plot
combine
Combine Ensembles of Trees
MDSplot
Multi-dimensional Scaling Plot of Proximity matrix from randomForest