tunable()
determines which parameters in an object can be tuned along
with information about the parameters.
# S3 method for model_spec tunable(x, ...) # S3 method for workflow tunable(x, ...) # S3 method for linear_reg tunable(x, ...) # S3 method for logistic_reg tunable(x, ...) # S3 method for multinomial_reg tunable(x, ...) # S3 method for boost_tree tunable(x, ...) # S3 method for rand_forest tunable(x, ...) # S3 method for mars tunable(x, ...) # S3 method for decision_tree tunable(x, ...) # S3 method for svm_poly tunable(x, ...)
x | An object, such as a workflow or |
---|---|
... | Not currently used. |
A tibble with a column for the parameter name
, information on the
default method for generating a corresponding parameter object, the
source
of the parameter (e.g. "model_spec", etc.), and the component
within the source. For the component
column, a little more specificity is
given about the location of the parameter (e.g. "boost_tree" for models).
The component_id
column contains the unique step id
field or, for
models, a logical for whether the model specification argument was a main
parameter or one associated with the engine.
For a model specification, an engine must be chosen.
If the object has no tunable parameters, a tibble with no rows is returned.
The information about the default parameter object takes the form of a
named list with an element for the function call and an optional element for
the source of the function (e.g. the dials
package). For model
specifications, if the parameter is unknown to the underlying tunable
method, a NULL
is returned.
#> # A tibble: 8 x 5 #> name call_info source component component_id #> <chr> <list> <chr> <chr> <chr> #> 1 tree_depth <named list [2]> model_spec boost_tree main #> 2 trees <named list [2]> model_spec boost_tree main #> 3 learn_rate <named list [2]> model_spec boost_tree main #> 4 mtry <named list [2]> model_spec boost_tree main #> 5 min_n <named list [2]> model_spec boost_tree main #> 6 loss_reduction <named list [2]> model_spec boost_tree main #> 7 sample_size <named list [2]> model_spec boost_tree main #> 8 stop_iter <named list [2]> model_spec boost_tree main#> # A tibble: 4 x 5 #> name call_info source component component_id #> <chr> <list> <chr> <chr> <chr> #> 1 trees <named list [3]> model_spec boost_tree main #> 2 min_n <named list [2]> model_spec boost_tree main #> 3 sample_size <named list [2]> model_spec boost_tree main #> 4 rules <NULL> model_spec boost_tree engine# }