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randomForest (version 4.7-1.1)
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)
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Install
install.packages('randomForest')
Monthly Downloads
132,008
Version
4.7-1.1
License
GPL (>= 2)
Maintainer
Andy Liaw
Last Published
May 23rd, 2022
Functions in randomForest (4.7-1.1)
Search all functions
importance
Extract variable importance measure
na.roughfix
Rough Imputation of Missing Values
outlier
Compute outlying measures
classCenter
Prototypes of groups.
imports85
The Automobile Data
getTree
Extract a single tree from a forest.
MDSplot
Multi-dimensional Scaling Plot of Proximity matrix from randomForest
margin
Margins of randomForest Classifier
grow
Add trees to an ensemble
combine
Combine Ensembles of Trees
rfcv
Random Forest Cross-Valdidation for feature selection
plot.randomForest
Plot method for randomForest objects
partialPlot
Partial dependence plot
treesize
Size of trees in an ensemble
randomForest
Classification and Regression with Random Forest
predict.randomForest
predict method for random forest objects
varUsed
Variables used in a random forest
rfImpute
Missing Value Imputations by randomForest
tuneRF
Tune randomForest for the optimal mtry parameter
varImpPlot
Variable Importance Plot
rfNews
Show the NEWS file