Breiman and Cutlers Random Forests for Classification and Regression

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Documentation for package ‘randomForest’ version 4.7-1.2

• DESCRIPTION file.
• Package NEWS.

Help Pages

classCenter	Prototypes of groups.
combine	Combine Ensembles of Trees
getTree	Extract a single tree from a forest.
grow	Add trees to an ensemble
grow.default	Add trees to an ensemble
grow.randomForest	Add trees to an ensemble
importance	Extract variable importance measure
importance.default	Extract variable importance measure
importance.randomForest	Extract variable importance measure
imports85	The Automobile Data
margin	Margins of randomForest Classifier
margin.default	Margins of randomForest Classifier
margin.randomForest	Margins of randomForest Classifier
MDSplot	Multi-dimensional Scaling Plot of Proximity matrix from randomForest
na.roughfix	Rough Imputation of Missing Values
na.roughfix.data.frame	Rough Imputation of Missing Values
na.roughfix.default	Rough Imputation of Missing Values
outlier	Compute outlying measures
outlier.default	Compute outlying measures
outlier.randomForest	Compute outlying measures
partialPlot	Partial dependence plot
partialPlot.default	Partial dependence plot
partialPlot.randomForest	Partial dependence plot
plot.margin	Margins of randomForest Classifier
plot.randomForest	Plot method for randomForest objects
predict.randomForest	predict method for random forest objects
print.randomForest	Classification and Regression with Random Forest
randomForest	Classification and Regression with Random Forest
randomForest.default	Classification and Regression with Random Forest
randomForest.formula	Classification and Regression with Random Forest
rfcv	Random Forest Cross-Valdidation for feature selection
rfImpute	Missing Value Imputations by randomForest
rfImpute.default	Missing Value Imputations by randomForest
rfImpute.formula	Missing Value Imputations by randomForest
rfNews	Show the NEWS file
treesize	Size of trees in an ensemble
tuneRF	Tune randomForest for the optimal mtry parameter
varImpPlot	Variable Importance Plot
varUsed	Variables used in a random forest