tuneRF
From randomForest v4.612
by Andy Liaw
Tune randomForest for the optimal mtry parameter
Starting with the default value of mtry, search for the optimal value (with respect to OutofBag 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
Examples
library(randomForest)
data(fgl, package="MASS")
fgl.res < tuneRF(fgl[,10], fgl[,10], stepFactor=1.5)
Community examples
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