This function creates a key that connects the identifiers users make for tuning parameter names, the standardized parsnip parameter names, and the argument names to the underlying fit function for the engine.
Arguments
- object
A workflow or parsnip model specification.
- as_tibble
A logical. Should the results be in a tibble (the default) or in a list that can facilitate renaming grid objects?
Value
A tibble with columns user, parsnip, and engine, or a list
with named character vectors user_to_parsnip and parsnip_to_engine.
Examples
mod <-
linear_reg(penalty = tune("regularization"), mixture = tune()) %>%
set_engine("glmnet")
mod %>% .model_param_name_key()
#> # A tibble: 2 × 3
#> user parsnip engine
#> <chr> <chr> <chr>
#> 1 regularization penalty lambda
#> 2 mixture mixture alpha
rn <- mod %>% .model_param_name_key(as_tibble = FALSE)
rn
#> $user_to_parsnip
#> penalty mixture
#> "regularization" "mixture"
#>
#> $parsnip_to_engine
#> lambda alpha
#> "penalty" "mixture"
#>
grid <- tidyr::crossing(regularization = c(0, 1), mixture = (0:3) / 3)
grid %>%
dplyr::rename(!!!rn$user_to_parsnip)
#> # A tibble: 8 × 2
#> penalty mixture
#> <dbl> <dbl>
#> 1 0 0
#> 2 0 0.333
#> 3 0 0.667
#> 4 0 1
#> 5 1 0
#> 6 1 0.333
#> 7 1 0.667
#> 8 1 1
grid %>%
dplyr::rename(!!!rn$user_to_parsnip) %>%
dplyr::rename(!!!rn$parsnip_to_engine)
#> # A tibble: 8 × 2
#> lambda alpha
#> <dbl> <dbl>
#> 1 0 0
#> 2 0 0.333
#> 3 0 0.667
#> 4 0 1
#> 5 1 0
#> 6 1 0.333
#> 7 1 0.667
#> 8 1 1