tuneMtryFast {tuneRanger}

tuneMtryFast

Description

Similar to tuneRF in randomForest but for ranger.

Usage

tuneMtryFast(
  formula = NULL,
  data = NULL,
  dependent.variable.name = NULL,
  mtryStart = floor(sqrt(ncol(data) - 1)),
  num.treesTry = 50,
  stepFactor = 2,
  improve = 0.05,
  trace = TRUE,
  plot = TRUE,
  doBest = FALSE,
  ...
)

Arguments

formula

Object of class formula or character describing the model to fit. Interaction terms supported only for numerical variables.

data

Training data of class data.frame, matrix, dgCMatrix (Matrix) or gwaa.data (GenABEL).

dependent.variable.name

Name of dependent variable, needed if no formula given. For survival forests this is the time variable.

mtryStart

starting value of mtry; default is the same as in ranger

num.treesTry

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 ranger

Details

Provides fast tuning for the mtry hyperparameter.

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

Examples

library(tuneRanger)

data(iris)
res <- tuneMtryFast(Species ~ ., data = iris, stepFactor = 1.5)