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.
Usage
# 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, ...)
Arguments
- object
A
model_spec
or arecipe
.- full
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.
Value
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
).
Examples
# List all possible varying args for the random forest spec
rand_forest() %>% varying_args()
#> Warning: `varying_args()` was deprecated in parsnip 0.1.8.
#> ℹ Please use `tune_args()` instead.
#> # A tibble: 3 × 4
#> name varying id type
#> <chr> <lgl> <chr> <chr>
#> 1 mtry FALSE rand_forest model_spec
#> 2 trees FALSE rand_forest model_spec
#> 3 min_n FALSE rand_forest model_spec
# mtry is now recognized as varying
rand_forest(mtry = varying()) %>% varying_args()
#> # A tibble: 3 × 4
#> name varying id type
#> <chr> <lgl> <chr> <chr>
#> 1 mtry TRUE rand_forest model_spec
#> 2 trees FALSE rand_forest model_spec
#> 3 min_n FALSE rand_forest model_spec
# Even engine specific arguments can vary
rand_forest() %>%
set_engine("ranger", sample.fraction = varying()) %>%
varying_args()
#> # A tibble: 4 × 4
#> name varying id type
#> <chr> <lgl> <chr> <chr>
#> 1 mtry FALSE rand_forest model_spec
#> 2 trees FALSE rand_forest model_spec
#> 3 min_n FALSE rand_forest model_spec
#> 4 sample.fraction TRUE rand_forest model_spec
# List only the arguments that actually vary
rand_forest() %>%
set_engine("ranger", sample.fraction = varying()) %>%
varying_args(full = FALSE)
#> # A tibble: 1 × 4
#> name varying id type
#> <chr> <lgl> <chr> <chr>
#> 1 sample.fraction TRUE rand_forest model_spec
rand_forest() %>%
set_engine(
"randomForest",
strata = Class,
sampsize = varying()
) %>%
varying_args()
#> # A tibble: 5 × 4
#> name varying id type
#> <chr> <lgl> <chr> <chr>
#> 1 mtry FALSE rand_forest model_spec
#> 2 trees FALSE rand_forest model_spec
#> 3 min_n FALSE rand_forest model_spec
#> 4 strata FALSE rand_forest model_spec
#> 5 sampsize TRUE rand_forest model_spec