Hi! This my first time using this forum so I'm hoping someone can help me. Using the code from this #TidyTuesday post (https://juliasilge.com/blog/last-airbender/), I'm getting the following error. I'm using recipes version 0.1.13. In March, there was a question very similar to this on this forum. The solution was to update recipes. I believe I'm using the most recent version of recipes.
set.seed(234)
avatar_folds <- vfold_cv(TCC9to17_2017, strata = retained)
avatar_folds
avatar_rec <- recipe(retained ~ ., data = TCC9to17_2017) %>%
step_corr(all_numeric()) %>%
step_YeoJohnson(all_numeric()) %>%
step_dummy(all_predictors(), -all_numeric()) %>%
step_zv(all_numeric()) %>%
step_normalize(all_numeric()) %>%
step_upsample(retained, skip = TRUE)
avatar_prep <- prep(avatar_rec)
avatar_prep
juice(avatar_prep)
rf_spec <- rand_forest(trees = 1000) %>%
set_engine("ranger") %>%
set_mode("classification")
rf_spec
avatar_wf <- workflow() %>%
add_recipe(avatar_rec)
avatar_wf
doParallel::registerDoParallel()
set.seed(1234)
rf_rs <- avatar_wf %>%
add_model(rf_spec) %>%
fit_resamples(
resamples = avatar_folds,
metrics = metric_set(roc_auc, accuracy, sens, spec),
control = control_grid(save_pred = TRUE)
)
#############################
Warning message:
All models failed in [fit_resamples()]. See the `.notes` column.
> rf_rs
# Resampling results
# 10-fold cross-validation using stratification
# A tibble: 10 x 5
splits id .metrics .notes .predictions
<list> <chr> <list> <list> <list>
1 <split [1.1K/128]> Fold01 <NULL> <tibble [1 x 1]> <NULL>
2 <split [1.1K/128]> Fold02 <NULL> <tibble [1 x 1]> <NULL>
3 <split [1.1K/128]> Fold03 <NULL> <tibble [1 x 1]> <NULL>
4 <split [1.1K/128]> Fold04 <NULL> <tibble [1 x 1]> <NULL>
5 <split [1.1K/128]> Fold05 <NULL> <tibble [1 x 1]> <NULL>
6 <split [1.1K/128]> Fold06 <NULL> <tibble [1 x 1]> <NULL>
7 <split [1.1K/128]> Fold07 <NULL> <tibble [1 x 1]> <NULL>
8 <split [1.1K/128]> Fold08 <NULL> <tibble [1 x 1]> <NULL>
9 <split [1.1K/127]> Fold09 <NULL> <tibble [1 x 1]> <NULL>
10 <split [1.2K/126]> Fold10 <NULL> <tibble [1 x 1]> <NULL>
Warning message:
This tuning result has notes. Example notes on model fitting include:
recipe: Error: could not find function "all_numeric"
recipe: Error: could not find function "all_numeric"
recipe: Error: could not find function "all_numeric"