tune_grid() and gam model incl. gam-formula

[John_Rambo]

Question:
How to use tune_grid() and a gam model (gen_additive_mod()) incl. gam-formula. please provide a code-snippet. thx.

[Max]

Here's an example:

library(tidymodels)
#> Registered S3 method overwritten by 'tune':
#>   method                   from   
#>   required_pkgs.model_spec parsnip
#> Warning: package 'broom' was built under R version 4.1.2
tidymodels_prefer()

gam_spec <- gen_additive_mod(select_features = tune()) %>% set_mode("regression")

gam_wflow <- 
  workflow() %>% 
  # smoothing must be specified here:
  add_model(gam_spec, formula = mpg ~ s(disp) + wt + gear) %>% 
  add_variables(predictors = c(everything()), outcomes = mpg)

set.seed(1)
car_folds <- bootstraps(mtcars, times = 5)

gam_res <- 
  gam_wflow %>% tune_grid(resamples = car_folds)

show_best(gam_res, metric = "rmse")
#> # A tibble: 2 × 7
#>   select_features .metric .estimator  mean     n std_err .config             
#>   <lgl>           <chr>   <chr>      <dbl> <int>   <dbl> <chr>               
#> 1 FALSE           rmse    standard    3.48     5   0.848 Preprocessor1_Model2
#> 2 TRUE            rmse    standard    3.48     5   0.848 Preprocessor1_Model1

^{Created on 2022-01-24 by the reprex package (v2.0.1)}

You can't optimize the smoothing parameters in tune_grid(). You could set up multiple workflows with different smoothing specifications and use a workflow set to try different ideas.

[John_Rambo]

Thank you Max. Post must be at least 20 characters.