I was following the guide here https://www.tidymodels.org/start/tuning/ on tuning models using tidymodels but wanted to try it using a bagged tree model. However, when I try and tune the bagged tree model I get the warning message:
Warning message: All models failed in tune_grid(). See the .notes
In the notes column each entry is:
"internal: Error in rlang::env_get(mod_env, items): argument \"default\" is missing, with no default"
The only thing different about my code from the guide is the model type and the model will fit if I specify the parameters directly, but I am unable to tune the model and I'm not sure why. Nor can I find any posts of others having a similar problem with baguette or rpart using tune_grid.
library(baguette) bag_spec <- bag_tree(tree_depth = tune()) %>% set_mode("regression") %>% set_engine("rpart", times = 25) bag_grid <- grid_regular( tree_depth(), levels = 10 ) bag_wf <- workflow() %>% add_formula(QUAL_SCORE_y0 ~ .) %>% add_model(bag_spec) vb_folds <- vfold_cv(df_training) doParallel::registerDoParallel() bag_res <- tune_grid( bag_wf, resamples = vb_folds, grid = bag_grid )