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randomForest (version 4.5-32)
Breiman and Cutler's random forests for classification and regression
Description
Classification and regression based on a forest of trees using random inputs.
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Install
install.packages('randomForest')
Monthly Downloads
77,306
Version
4.5-32
License
GPL (>= 2)
Maintainer
Andy Liaw
Last Published
October 16th, 2009
Functions in randomForest (4.5-32)
Search functions
tuneRF
Tune randomForest for the optimal mtry parameter
predict.randomForest
predict method for random forest objects
margin
Margins of randomForest Classifier
imports85
The Automobile Data
combine
Combine Ensembles of Trees
na.roughfix
Rough Imputation of Missing Values
varUsed
Variables used in a random forest
MDSplot
Multi-dimensional Scaling Plot of Proximity matrix from randomForest
treesize
Size of trees in an ensemble
plot.randomForest
Plot method for randomForest objects
getTree
Extract a single tree from a forest.
rfImpute
Missing Value Imputations by randomForest
outlier
Compute outlying measures
grow
Add trees to an ensemble
classCenter
Prototypes of groups.
importance
Extract variable importance measure
varImpPlot
Variable Importance Plot
partialPlot
Partial dependence plot
randomForest
Classification and Regression with Random Forest
rfNews
Show the NEWS file