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randomForest (version 4.5-27)
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
4.5-27
License
GPL version 2 or later
Maintainer
Andy Liaw
Last Published
September 22nd, 2024
Functions in randomForest (4.5-27)
Search all functions
partialPlot
Partial dependence plot
rfImpute
Missing Value Imputations by randomForest
importance
Extract variable importance measure
combine
Combine Ensembles of Trees
rfNews
Show the NEWS file
imports85
The Automobile Data
treesize
Size of trees in an ensemble
varUsed
Variables used in a random forest
grow
Add trees to an ensemble
classCenter
Prototypes of groups.
plot.randomForest
Plot method for randomForest objects
varImpPlot
Variable Importance Plot
MDSplot
Multi-dimensional Scaling Plot of Proximity matrix from randomForest
margin
Margins of randomForest Classifier
getTree
Extract a single tree from a forest.
outlier
Compute outlying measures
predict.randomForest
predict method for random forest objects
tuneRF
Tune randomForest for the optimal mtry parameter
na.roughfix
Rough Imputation of Missing Values
randomForest
Classification and Regression with Random Forest