Nothing
Code
res <- tune_cluster(wflow, resamples = folds, grid = grid, control = control,
metrics = metrics)
Message
i Fold1: preprocessor 1/3
v Fold1: preprocessor 1/3
i Fold1: preprocessor 1/3, model 1/3
v Fold1: preprocessor 1/3, model 1/3
i Fold1: preprocessor 1/3, model 1/3 (predictions)
i Fold1: preprocessor 1/3, model 2/3
v Fold1: preprocessor 1/3, model 2/3
i Fold1: preprocessor 1/3, model 2/3 (predictions)
i Fold1: preprocessor 1/3, model 3/3
v Fold1: preprocessor 1/3, model 3/3
i Fold1: preprocessor 1/3, model 3/3 (predictions)
i Fold1: preprocessor 2/3
v Fold1: preprocessor 2/3
i Fold1: preprocessor 2/3, model 1/3
v Fold1: preprocessor 2/3, model 1/3
i Fold1: preprocessor 2/3, model 1/3 (predictions)
i Fold1: preprocessor 2/3, model 2/3
v Fold1: preprocessor 2/3, model 2/3
i Fold1: preprocessor 2/3, model 2/3 (predictions)
i Fold1: preprocessor 2/3, model 3/3
v Fold1: preprocessor 2/3, model 3/3
i Fold1: preprocessor 2/3, model 3/3 (predictions)
i Fold1: preprocessor 3/3
v Fold1: preprocessor 3/3
i Fold1: preprocessor 3/3, model 1/3
v Fold1: preprocessor 3/3, model 1/3
i Fold1: preprocessor 3/3, model 1/3 (predictions)
i Fold1: preprocessor 3/3, model 2/3
v Fold1: preprocessor 3/3, model 2/3
i Fold1: preprocessor 3/3, model 2/3 (predictions)
i Fold1: preprocessor 3/3, model 3/3
v Fold1: preprocessor 3/3, model 3/3
i Fold1: preprocessor 3/3, model 3/3 (predictions)
i Fold2: preprocessor 1/3
v Fold2: preprocessor 1/3
i Fold2: preprocessor 1/3, model 1/3
v Fold2: preprocessor 1/3, model 1/3
i Fold2: preprocessor 1/3, model 1/3 (predictions)
i Fold2: preprocessor 1/3, model 2/3
v Fold2: preprocessor 1/3, model 2/3
i Fold2: preprocessor 1/3, model 2/3 (predictions)
i Fold2: preprocessor 1/3, model 3/3
v Fold2: preprocessor 1/3, model 3/3
i Fold2: preprocessor 1/3, model 3/3 (predictions)
i Fold2: preprocessor 2/3
v Fold2: preprocessor 2/3
i Fold2: preprocessor 2/3, model 1/3
v Fold2: preprocessor 2/3, model 1/3
i Fold2: preprocessor 2/3, model 1/3 (predictions)
i Fold2: preprocessor 2/3, model 2/3
v Fold2: preprocessor 2/3, model 2/3
i Fold2: preprocessor 2/3, model 2/3 (predictions)
i Fold2: preprocessor 2/3, model 3/3
v Fold2: preprocessor 2/3, model 3/3
i Fold2: preprocessor 2/3, model 3/3 (predictions)
i Fold2: preprocessor 3/3
v Fold2: preprocessor 3/3
i Fold2: preprocessor 3/3, model 1/3
v Fold2: preprocessor 3/3, model 1/3
i Fold2: preprocessor 3/3, model 1/3 (predictions)
i Fold2: preprocessor 3/3, model 2/3
v Fold2: preprocessor 3/3, model 2/3
i Fold2: preprocessor 3/3, model 2/3 (predictions)
i Fold2: preprocessor 3/3, model 3/3
v Fold2: preprocessor 3/3, model 3/3
i Fold2: preprocessor 3/3, model 3/3 (predictions)
Code
cars_res <- tune_cluster(helper_objects$kmeans_mod, ~z, resamples = data_folds,
grid = cars_grid, control = tune::control_grid(extract = function(x) {
1
}, save_pred = TRUE))
Message
x Fold1: preprocessor 1/1: Error in `get_all_predictors()`:
! The following predi...
x Fold2: preprocessor 1/1: Error in `get_all_predictors()`:
! The following predi...
Condition
Warning:
All models failed. See the `.notes` column.
Code
tune_cluster(helper_objects$rec_tune_1, helper_objects$kmeans_mod_no_tune,
rsample::vfold_cv(mtcars, v = 2))
Condition
Error in `tune_cluster()`:
! The first argument to [tune_cluster()] should be either a model or workflow.
Code
tune_cluster(mpg ~ ., helper_objects$kmeans_mod_no_tune, rsample::vfold_cv(
mtcars, v = 2))
Condition
Error in `tune_cluster()`:
! The first argument to [tune_cluster()] should be either a model or workflow.
Code
tune_cluster(wflow, resamples = folds, grid = 3, something = "wrong")
Condition
Warning:
The `...` are not used in this function but one or more objects were passed: 'something'
Output
# Tuning results
# 2-fold cross-validation
# A tibble: 2 x 4
splits id .metrics .notes
<list> <chr> <list> <list>
1 <split [16/16]> Fold1 <tibble [4 x 5]> <tibble [0 x 3]>
2 <split [16/16]> Fold2 <tibble [4 x 5]> <tibble [0 x 3]>
Code
tmp <- tune::show_best(res)
Condition
Warning:
No value of `metric` was given; metric 'sse_within_total' will be used.
Code
tmp <- tune::select_best(res)
Condition
Warning:
No value of `metric` was given; metric 'sse_within_total' will be used.
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.