library(tidymodels)
library(tailor)

set.seed(121)
ad_split <- initial_split(ad_data, strata = Class)
ad_tr <- training(ad_split)
ad_te <- testing(ad_split)
ad_rs <- vfold_cv(ad_tr, repeats = 10, strata = Class)

rf_spec <- rand_forest() %>% set_mode("classification")

rf_bl_wflow <- 
  workflow(Class ~ ., rf_spec)

post_high <- tailor() %>% adjust_probability_threshold(0.99)
post_low  <- tailor() %>% adjust_probability_threshold(0.01)

high_wflow <- 
  rf_bl_wflow %>% 
  add_tailor(post_high)

low_wflow <- 
  rf_bl_wflow %>% 
  add_tailor(post_low)

cls_mtr <- metric_set(roc_auc, brier_class, sensitivity, specificity, j_index, mcc)

set.seed(1)
rf_bl_res <- rf_bl_wflow %>% fit_resamples(ad_rs, metrics = cls_mtr)

set.seed(1)
high_res <- high_wflow %>% fit_resamples(ad_rs, metrics = cls_mtr)

set.seed(1)
low_res <- low_wflow %>% fit_resamples(ad_rs, metrics = cls_mtr)

identical(collect_metrics(rf_bl_res), collect_metrics(low_res))
#> [1] FALSE
identical(collect_metrics(high_res), collect_metrics(low_res))
#> [1] FALSE