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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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Install
install.packages('randomForest')
Monthly Downloads
147,820
Version
4.7-1.2
License
GPL (>= 2)
Maintainer
Andy Liaw
Last Published
September 22nd, 2024
Functions in randomForest (4.7-1.2)
Search all functions
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