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, ...)
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.
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