Learning rate — learn

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 = transform_log10())

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::transform_log10() or scales::transform_reciprocal(). If not provided, the default is used which matches the units used in range. If no transformation, NULL.

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.

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