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randomForest

Breiman and Cutler's Random Forests for Classification and Regression

Classification and regression based on a forest of trees using random inputs, based on Breiman (2001) <DOI:10.1023/A:1010933404324>.

Functions (21)

MDSplot

Multi-dimensional Scaling Plot of Proximity matrix from randomForest

classCenter

Prototypes of groups.

combine

Combine Ensembles of Trees

getTree

Extract a single tree from a forest.

grow

Add trees to an ensemble

importance

Extract variable importance measure

imports85

The Automobile Data

margin

Margins of randomForest Classifier

na.roughfix

Rough Imputation of Missing Values

outlier

Compute outlying measures

partialPlot

Partial dependence plot

plot.randomForest

Plot method for randomForest objects

predict.randomForest

predict method for random forest objects

randomForest

Classification and Regression with Random Forest

rfImpute

Missing Value Imputations by randomForest

rfNews

Show the NEWS file

rfcv

Random Forest Cross-Valdidation for feature selection

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

randomForest

Breiman and Cutler's Random Forests for Classification and Regression

v4.6-14

GPL (>= 2)

Authors

Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener.

Initial release

2018-03-22

randomForest

Functions (21)

randomForest

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