Find recommended methods for generating parameter values
tunable() determines which parameters in an object can be tuned along
with information about the parameters.
## S3 method for class 'recipe' tunable(x, ...) ## S3 method for class 'step' tunable(x, ...) ## S3 method for class 'check' tunable(x, ...)
x |
A recipe, recipe step, or recipe check object |
... |
Not currently used. |
These functions define what parameters can be tuned for specific steps.
They also define the recommended objects from the dials package that can
be used to generate new parameter values and other characteristics.
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).
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. "recipe", 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. "step_normalize" for recipes).
The component_id column contains the unique step id field.
library(recipes) recipe(mpg ~ ., data = mtcars) %>% step_knnimpute(all_predictors()) %>% step_pca(all_numeric_predictors()) %>% tunable() recipe(mpg ~ ., data = mtcars) %>% step_normalize(all_numeric_predictors()) %>% tunable()
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