The proportion of predictors that will be randomly sampled at each split when creating tree models.

## Usage

mtry_prop(range = c(0.1, 1), trans = NULL)

## 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.

## Value

A dials object with classes "quant_param" and "param". The range element of the object is always converted to a list with elements "lower" and "upper".

## Interpretation

mtry_prop() is a variation on mtry() where the value is interpreted as the proportion of predictors that will be randomly sampled at each split rather than the count.

This parameter is not intended for use in accommodating engines that take in this argument as a proportion; mtry is often a main model argument rather than an engine-specific argument, and thus should not have an engine-specific interface.

When wrapping modeling engines that interpret mtry in its sense as a proportion, use the mtry() parameter in parsnip::set_model_arg() and process the passed argument in an internal wrapping function as mtry / number_of_predictors. In addition, introduce a logical argument counts to the wrapping function, defaulting to TRUE, that indicates whether to interpret the supplied argument as a count rather than a proportion.

For an example implementation, see parsnip::xgb_train().

mtry_prop()