The number of predictors that will be randomly sampled at each split when creating tree models.
mtry(range = c(1L, unknown()), trans = NULL)mtry_long(range = c(0L, unknown()), trans = log10_trans())
A two-element vector holding the defaults for the smallest and largest possible values, respectively.
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.
This parameter is used for regularized or penalized models such as
parsnip::rand_forest() and others. mtry_long() has the values on the
log10 scale and is helpful when the data contain a large number of predictors.
Since the scale of the parameter depends on the number of columns in the
data set, the upper bound is set to unknown but can be filled in via the
finalize() method.
# NOT RUN {
mtry(c(1L, 10L)) # in original units
mtry_long(c(0, 5)) # in log10 units
# }
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