setup.Ranger: Set s_Ranger parameters

In egenn/rtemis: Machine Learning and Visualization

Set s_Ranger parameters

Description

Set s_Ranger parameters

Usage

setup.Ranger(
  n.trees = 1000,
  min.node.size = 1,
  mtry = NULL,
  grid.resample.params = setup.resample("kfold", 5),
  ifw = TRUE,
  upsample = FALSE,
  downsample = FALSE,
  resample.seed = NULL,
  ...
)

Arguments

n.trees	Integer: Number of trees to grow. Default = 1000
min.node.size	[gS] Integer: Minimum node size
mtry	[gS] Integer: Number of features sampled randomly at each split. Defaults to square root of n of features for classification, and a third of n of features for regression.
grid.resample.params	List: Output of setup.resample defining grid search parameters.
ifw	Logical: If TRUE, apply inverse frequency weighting (for Classification only). Note: If weights are provided, ifw is not used.
upsample	Logical: If TRUE, upsample training set cases not belonging in majority outcome group
downsample	Logical: If TRUE, downsample majority class to match size of minority class
resample.seed	Integer: If provided, will be used to set the seed during upsampling. Default = NULL (random seed)
...	Additional arguments to be passed to ranger::ranger

egenn/rtemis documentation built on May 4, 2024, 7:40 p.m.