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Code
tune:::check_grid(chi_wflow, chi_wflow)
Condition
Error in `tune:::check_grid()`:
! `grid` should be a positive integer or a data frame.
Unknown grid columns are caught
Code
tune:::check_grid(grid, workflow)
Condition
Error in `tune:::check_grid()`:
! The provided `grid` has the following parameter columns that have not been marked for tuning by `tune()`: 'other1', 'other2'.
Missing required grid columns are caught
Code
tune:::check_grid(grid, workflow)
Condition
Error in `tune:::check_grid()`:
! The provided `grid` is missing the following parameter columns that have been marked for tuning by `tune()`: 'deg_free'.
workflow objects
Code
tune:::check_workflow(x = wflow_2, check_dials = TRUE)
Condition
Error in `tune:::check_workflow()`:
! The workflow has arguments whose ranges are not finalized: 'mtry'
Code
tune:::check_workflow(wflow_3)
Condition
Error in `tune:::check_workflow()`:
! A formula, recipe, or variables preprocessor is required.
Code
tune:::check_workflow(wflow_4)
Condition
Error in `tune:::check_workflow()`:
! A parsnip model is required.
yardstick objects
Code
tune:::check_metrics(yardstick::rmse, chi_wflow)
Condition
Error in `tune:::check_metrics()`:
! The `metrics` argument should be the results of [yardstick::metric_set()].
metrics must match the parsnip engine
Code
tune:::check_metrics(metric_set1, workflow1)
Condition
Error in `tune:::check_metrics()`:
! The parsnip model has `mode = 'regression'`, but `metrics` is a metric set for class / probability metrics.
Code
tune:::check_metrics(metric_set2, workflow2)
Condition
Error in `tune:::check_metrics()`:
! The parsnip model has `mode = 'classification'`, but `metrics` is a metric set for regression metrics.
Code
control_grid(verbose = 1)
Condition
Error in `val_class_and_single()`:
! Argument 'verbose' should be a single logical value in `control_grid()`
Code
control_grid(verbose = rep(TRUE, 2))
Condition
Error in `val_class_and_single()`:
! Argument 'verbose' should be a single logical value in `control_grid()`
Code
control_grid(allow_par = 1)
Condition
Error in `val_class_and_single()`:
! Argument 'allow_par' should be a single logical value in `control_grid()`
Code
control_grid(save_pred = "no")
Condition
Error in `val_class_and_single()`:
! Argument 'save_pred' should be a single logical value in `control_grid()`
Code
control_grid(extract = Inf)
Condition
Error in `val_class_or_null()`:
! Argument 'extract' should be a function or NULL in `control_grid()`
Code
control_grid(pkgs = Inf)
Condition
Error in `val_class_or_null()`:
! Argument 'pkgs' should be a character or NULL in `control_grid()`
Code
control_bayes(verbose = 1)
Condition
Error in `val_class_and_single()`:
! Argument 'verbose' should be a single logical value in `control_bayes()`
Code
control_bayes(verbose = rep(TRUE, 2))
Condition
Error in `val_class_and_single()`:
! Argument 'verbose' should be a single logical value in `control_bayes()`
Code
control_bayes(no_improve = FALSE)
Condition
Error in `val_class_and_single()`:
! Argument 'no_improve' should be a single numeric or integer value in `control_bayes()`
Code
control_bayes(uncertain = FALSE)
Condition
Error in `val_class_and_single()`:
! Argument 'uncertain' should be a single numeric or integer value in `control_bayes()`
Code
control_bayes(seed = FALSE)
Condition
Error in `val_class_and_single()`:
! Argument 'seed' should be a single numeric or integer value in `control_bayes()`
Code
control_bayes(save_pred = "no")
Condition
Error in `val_class_and_single()`:
! Argument 'save_pred' should be a single logical value in `control_bayes()`
Code
control_bayes(extract = Inf)
Condition
Error in `val_class_or_null()`:
! Argument 'extract' should be a function or NULL in `control_bayes()`
Code
control_bayes(pkgs = Inf)
Condition
Error in `val_class_or_null()`:
! Argument 'pkgs' should be a character or NULL in `control_bayes()`
Code
control_bayes(time_limit = "a")
Condition
Error in `val_class_and_single()`:
! Argument 'time_limit' should be a single logical or numeric value in `control_bayes()`
Code
tmp <- control_bayes(no_improve = 2, uncertain = 5)
Message
! Uncertainty sample scheduled after 5 poor iterations but the search will stop after 2.
initial values
Code
tune:::check_initial(data.frame(), extract_parameter_set_dials(wflow_1),
wflow_1, mtfolds, yardstick::metric_set(yardstick::rsq), control_bayes())
Condition
Error in `tune:::check_initial()`:
! `initial` should be a positive integer or the results of [tune_grid()]
Acquisition function objects
Code
tune:::check_direction(1)
Condition
Error in `tune:::check_direction()`:
! `maximize` should be a single logical.
Code
tune:::check_direction(rep(TRUE, 2))
Condition
Error in `tune:::check_direction()`:
! `maximize` should be a single logical.
Code
tune:::check_best(FALSE)
Condition
Error in `tune:::check_best()`:
! `best` should be a single, non-missing numeric.
Code
tune:::check_best(rep(2, 2))
Condition
Error in `tune:::check_best()`:
! `best` should be a single, non-missing numeric.
Code
tune:::check_best(NA)
Condition
Error in `tune:::check_best()`:
! `best` should be a single, non-missing numeric.
check parameter finalization
Code
expect_error(p1 <- tune:::check_parameters(w1, data = mtcars, grid_names = character(
0)), regex = NA)
Message
i Creating pre-processing data to finalize unknown parameter: mtry
Code
expect_error(p2 <- tune:::check_parameters(w2, data = mtcars), regex = NA)
Message
i Creating pre-processing data to finalize unknown parameter: mtry
Code
expect_error(p3_a <- tune:::check_parameters(w3, data = mtcars), regex = NA)
Message
i Creating pre-processing data to finalize unknown parameter: mtry
Code
tune:::check_parameters(w4, data = mtcars)
Condition
Error in `tune:::check_parameters()`:
! Some tuning parameters require finalization but there are recipe parameters that require tuning. Please use `parameters()` to finalize the parameter ranges.