randomForest (version 4.5-35)

tuneRF: Tune randomForest for the optimal mtry parameter

Description

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

Usage

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

Arguments

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

Value

  • 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

randomForest

Examples

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

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