Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (4.7-1.2) of this package.
Take me there.
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.
Copy Link
Link to current version
Version
Version
4.7-1.2
4.7-1.1
4.7-1
4.6-14
4.6-12
4.6-10
4.6-7
4.6-6
4.6-5
4.6-4
4.6-3
4.6-2
4.6-1
4.5-36
4.5-35
4.5-34
4.5-33
4.5-32
4.5-31
4.5-30
4.5-28
4.5-27
4.5-26
4.5-25
4.5-24
4.5-23
4.5-22
4.5-21
4.5-20
4.5-19
4.5-18
4.5-16
4.5-15
4.5-12
4.5-11
4.5-10
4.5-9
4.5-8
4.5-7
4.5-6
4.5-4
4.5-2
4.5-1
4.4-2
4.4-1
4.3-3
4.3-2
4.3-0
4.0-7
4.0-1
3.9-6
3.4-5
3.4-4
3.4-1
3.3-8
3.3-7
3.3-6
3.3-4
3.3-2
1.0
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)
Search all functions
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