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randomForest (version 4.6-12)
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
92,025
Version
4.6-12
License
GPL (>= 2)
Maintainer
Andy Liaw
Last Published
October 7th, 2015
Functions in randomForest (4.6-12)
Search functions
margin
Margins of randomForest Classifier
grow
Add trees to an ensemble
MDSplot
Multi-dimensional Scaling Plot of Proximity matrix from randomForest
rfImpute
Missing Value Imputations by randomForest
getTree
Extract a single tree from a forest.
importance
Extract variable importance measure
varUsed
Variables used in a random forest
rfcv
Random Forest Cross-Valdidation for feature selection
rfNews
Show the NEWS file
partialPlot
Partial dependence plot
na.roughfix
Rough Imputation of Missing Values
classCenter
Prototypes of groups.
varImpPlot
Variable Importance Plot
treesize
Size of trees in an ensemble
tuneRF
Tune randomForest for the optimal mtry parameter
combine
Combine Ensembles of Trees
plot.randomForest
Plot method for randomForest objects
predict.randomForest
predict method for random forest objects
outlier
Compute outlying measures
randomForest
Classification and Regression with Random Forest
imports85
The Automobile Data