tuneRF

0th

Percentile

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.

Keywords
classif, tree
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

Aliases
  • tuneRF
Examples
library(randomForest) data(fgl, package="MASS") fgl.res <- tuneRF(fgl[,-10], fgl[,10], stepFactor=1.5)
Documentation reproduced from package randomForest, version 4.6-12, License: GPL (>= 2)

Community examples

Looks like there are no examples yet.