The problem
I'm having trouble with using groupwise metrics with finetune
Reproducible example
pacman::p_load(tidymodels, finetune)
data(ames)
diff_range <- function(x) {
diff(range(x$.estimate))
}
demographic_parity_ <-
new_groupwise_metric(
fn = detection_prevalence,
name = "demographic_parity",
aggregate = diff_range
)
m_set <- metric_set(demographic_parity_(Neighborhood))
set.seed(502)
ames_split <- initial_split(ames)
ames_train <- training(ames_split)
ames_folds <- vfold_cv(ames_train, v = 10)
rf_model <-
rand_forest(trees = tune()) %>%
set_engine("ranger") %>%
set_mode("classification")
rf_wflow <-
workflow() %>%
add_formula(
Lot_Shape ~ Year_Built + Bldg_Type + Latitude + Longitude
) %>%
add_model(rf_model)
grid <- parameters(trees(c(10, 100))) %>%
grid_max_entropy(size = 10)
tune_res_anova <- tune_race_anova(
rf_wflow,
ames_folds,
grid = grid,
metrics = m_set
)
#> Warning in max(best_config$B, na.rm = TRUE): no non-missing arguments to max;
#> returning -Inf
#> Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]): contrasts can be applied only to factors with 2 or more levels
#> Warning: package 'ranger' was built under R version 4.2.3
#> Warning: package 'rlang' was built under R version 4.2.3
#> Warning in max(best_config$B, na.rm = TRUE): no non-missing arguments to max;
#> returning -Inf
#> Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]): contrasts can be applied only to factors with 2 or more levelsCreated on 2024-08-30 with reprex v2.0.2
Session info
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
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#> collate Finnish_Finland.utf8
#> ctype Finnish_Finland.utf8
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#> date 2024-08-30
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#> ──────────────────────────────────────────────────────────────────────────────
The problem
I'm having trouble with using groupwise metrics with finetune
Reproducible example
Created on 2024-08-30 with reprex v2.0.2
Session info