Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (4.7-1.2) of this package.
Take me there.
randomForest (version 4.6-5)
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
93,657
Version
4.6-5
License
GPL (>= 2)
Maintainer
Andy Liaw
Last Published
January 4th, 2012
Functions in randomForest (4.6-5)
Search all functions
getTree
Extract a single tree from a forest.
classCenter
Prototypes of groups.
na.roughfix
Rough Imputation of Missing Values
randomForest
Classification and Regression with Random Forest
grow
Add trees to an ensemble
tuneRF
Tune randomForest for the optimal mtry parameter
varUsed
Variables used in a random forest
plot.randomForest
Plot method for randomForest objects
outlier
Compute outlying measures
combine
Combine Ensembles of Trees
rfNews
Show the NEWS file
rfImpute
Missing Value Imputations by randomForest
treesize
Size of trees in an ensemble
MDSplot
Multi-dimensional Scaling Plot of Proximity matrix from randomForest
varImpPlot
Variable Importance Plot
margin
Margins of randomForest Classifier
predict.randomForest
predict method for random forest objects
imports85
The Automobile Data
importance
Extract variable importance measure
partialPlot
Partial dependence plot
rfcv
Random Forest Cross-Valdidation for feature selection