The parameter is used in boosting methods (parsnip::boost_tree()) or some types of neural network optimization methods.

## Usage

learn_rate(range = c(-10, -1), trans = log10_trans())

## 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.

## Details

The parameter is used on the log10 scale. The units for the range function are on this scale.

learn_rate() corresponds to eta in xgboost.

## Examples

learn_rate()
#> Learning Rate (quantitative)
#> Transformer: log-10 [1e-100, Inf]
#> Range (transformed scale): [-10, -1]