tuneRF {randomForest}R Documentation

Tune randomForest for the optimal mtry parameter


Starting with the default value of mtry, search for the optimal value (with respect to Out-of-Bag error estimate) of mtry for randomForest.


tuneRF(x, y, mtryStart, ntreeTry=50, stepFactor=2, improve=0.05,
       trace=TRUE, plot=TRUE, doBest=FALSE, ...)


x matrix or data frame of predictor variables
y response vector (factor for classification, numeric for regression)
mtryStart starting value of mtry; default is the same as in randomForest
ntreeTry number of trees used at the tuning step
stepFactor at each iteration, mtry is inflated (or deflated) by this value
improve the (relative) improvement in OOB error must be by this much for the search to continue
trace whether to print the progress of the search
plot whether to plot the OOB error as function of mtry
doBest whether to run a forest using the optimal mtry found
... options to be given to randomForest


If doBest=FALSE (default), it returns a matrix whose first column contains the mtry values searched, and the second column the corresponding OOB error.
If doBest=TRUE, it returns the randomForest object produced with the optimal mtry.

See Also



data(fgl, package="MASS")
fgl.res <- tuneRF(fgl[,-10], fgl[,10], stepFactor=1.5)

[Package randomForest version 4.5-1 Index]