varying_args()
takes a model specification or a recipe and returns a tibble
of information on all possible varying arguments and whether or not they
are actually varying.
The id
column is determined differently depending on whether a model_spec
or a recipe
is used. For a model_spec
, the first class is used. For
a recipe
, the unique step id
is used.
# S3 method for model_spec
varying_args(object, full = TRUE, ...)# S3 method for recipe
varying_args(object, full = TRUE, ...)
# S3 method for step
varying_args(object, full = TRUE, ...)
A tibble with columns for the parameter name (name
), whether it
contains any varying value (varying
), the id
for the object (id
),
and the class that was used to call the method (type
).
A model_spec
or a recipe
.
A single logical. Should all possible varying parameters be
returned? If FALSE
, then only the parameters that
are actually varying are returned.
Not currently used.
# List all possible varying args for the random forest spec
rand_forest() %>% varying_args()
# mtry is now recognized as varying
rand_forest(mtry = varying()) %>% varying_args()
# Even engine specific arguments can vary
rand_forest() %>%
set_engine("ranger", sample.fraction = varying()) %>%
varying_args()
# List only the arguments that actually vary
rand_forest() %>%
set_engine("ranger", sample.fraction = varying()) %>%
varying_args(full = FALSE)
rand_forest() %>%
set_engine(
"randomForest",
strata = Class,
sampsize = varying()
) %>%
varying_args()
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