Nothing
Code
car_set_2 <- workflow_set(list(reg = mpg ~ ., nonlin = mpg ~ wt + 1 / sqrt(disp)),
list(lm = lr_spec), case_weights = non_wts) %>% workflow_map("fit_resamples",
resamples = vfold_cv(cars, v = 5))
Message <simpleMessage>
x Fold1: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
x Fold2: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
x Fold3: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
x Fold4: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
x Fold5: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
Warning <rlang_warning>
All models failed. Run `show_notes(.Last.tune.result)` for more information.
Message <simpleMessage>
x Fold1: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
x Fold2: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
x Fold3: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
x Fold4: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
x Fold5: preprocessor 1/1:
Error in `fit()`:
! `col` must select a classed case weights column, as determined by `h...
Warning <rlang_warning>
All models failed. Run `show_notes(.Last.tune.result)` for more information.
Code
class_note$note[1]
Output
[1] "Error in `fit()`:\n! `col` must select a classed case weights column, as determined by `hardhat::is_case_weights()`. For example, it could be a column created by `hardhat::frequency_weights()` or `hardhat::importance_weights()`."
Code
car_set_4 <- workflow_set(list(reg = mpg ~ ., nonlin = mpg ~ wt + 1 / sqrt(disp)),
list(lm = lr_spec), case_weights = boop) %>% workflow_map("fit_resamples",
resamples = vfold_cv(cars, v = 5))
Message <simpleMessage>
x Fold1: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
x Fold2: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
x Fold3: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
x Fold4: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
x Fold5: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
Warning <rlang_warning>
All models failed. Run `show_notes(.Last.tune.result)` for more information.
Message <simpleMessage>
x Fold1: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
x Fold2: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
x Fold3: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
x Fold4: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
x Fold5: preprocessor 1/1:
Error in `fit()`:
! Can't subset columns that don't exist.
x Column `boop` doesn't exist.
Warning <rlang_warning>
All models failed. Run `show_notes(.Last.tune.result)` for more information.
Code
class_note$note[1]
Output
[1] "Error in `fit()`:\n! Can't subset columns that don't exist.\nx Column `boop` doesn't exist."
# A workflow set/tibble: 3 x 4
wflow_id info option result
<chr> <list> <list> <list>
1 date_lm <tibble [1 x 4]> <opts[0]> <list [0]>
2 plus_holidays_lm <tibble [1 x 4]> <opts[0]> <list [0]>
3 plus_pca_lm <tibble [1 x 4]> <opts[0]> <list [0]>
# A workflow set/tibble: 3 x 4
wflow_id info option result
<chr> <list> <list> <list>
1 date_lm <tibble [1 x 4]> <opts[2]> <rsmp[+]>
2 plus_holidays_lm <tibble [1 x 4]> <opts[2]> <rsmp[+]>
3 plus_pca_lm <tibble [1 x 4]> <opts[3]> <tune[+]>
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