Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (4.7-1.2) of this package.
Take me there.
randomForest (version 4.6-14)
Breiman and Cutler's Random Forests for Classification and Regression
Description
Classification and regression based on a forest of trees using random inputs, based on Breiman (2001)
.
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
147,820
Version
4.6-14
License
GPL (>= 2)
Maintainer
Andy Liaw
Last Published
March 25th, 2018
Functions in randomForest (4.6-14)
Search all functions
grow
Add trees to an ensemble
MDSplot
Multi-dimensional Scaling Plot of Proximity matrix from randomForest
combine
Combine Ensembles of Trees
imports85
The Automobile Data
importance
Extract variable importance measure
na.roughfix
Rough Imputation of Missing Values
margin
Margins of randomForest Classifier
classCenter
Prototypes of groups.
getTree
Extract a single tree from a forest.
outlier
Compute outlying measures
varImpPlot
Variable Importance Plot
rfcv
Random Forest Cross-Valdidation for feature selection
rfImpute
Missing Value Imputations by randomForest
partialPlot
Partial dependence plot
rfNews
Show the NEWS file
treesize
Size of trees in an ensemble
plot.randomForest
Plot method for randomForest objects
predict.randomForest
predict method for random forest objects
randomForest
Classification and Regression with Random Forest
tuneRF
Tune randomForest for the optimal mtry parameter
varUsed
Variables used in a random forest