These parameters are auxiliary to random forest models that use the "ranger" engine. They correspond to tuning parameters that would be specified using set_engine("ranger", ...).

## Usage

regularization_factor(range = c(0, 1), trans = NULL)

regularize_depth(values = c(TRUE, FALSE))

significance_threshold(range = c(-10, 0), trans = log10_trans())

lower_quantile(range = c(0, 1), trans = NULL)

splitting_rule(values = ranger_split_rules)

ranger_class_rules

ranger_reg_rules

ranger_split_rules

num_random_splits(range = c(1L, 15L), trans = NULL)

## Format

An object of class character of length 4.

An object of class character of length 3.

An object of class character of length 7.

## Arguments

range

A two-element vector holding the defaults for the smallest and largest possible values, respectively. If a transformation is specified, these values should be in the transformed units.

trans

A trans object from the scales package, such as scales::log10_trans() or scales::reciprocal_trans(). If not provided, the default is used which matches the units used in range. If no transformation, NULL.

values

For splitting_rule(), a character string of possible values. See ranger_split_rules, ranger_class_rules, and ranger_reg_rules for appropriate values. For regularize_depth(), either TRUE or FALSE.

## Details

To use these, check ?ranger::ranger to see how they are used. Some are conditional on others. For example, significance_threshold(), num_random_splits(), and others are only used when splitting_rule = "extratrees".

## Examples

regularization_factor()
#> Gain Penalization (quantitative)
#> Range: [0, 1]
regularize_depth()
#> Regularize Tree Depth?  (qualitative)
#> 2 possible values include:
#> TRUE and FALSE