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 thescales
package, such asscales::transform_log10()
orscales::transform_reciprocal()
. If not provided, the default is used which matches the units used inrange
. 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()
.