tailor.md
In tailor: Iterative Steps for Postprocessing Model Predictions

tailor printing

Code
  tailor()
Message

  -- tailor ----------------------------------------------------------------------
  A postprocessor with 0 adjustments.

Code
  tailor()
Message

  -- tailor ----------------------------------------------------------------------
  A postprocessor with 0 adjustments.

Code
  adjust_probability_threshold(tailor(), 0.2)
Message

  -- tailor ----------------------------------------------------------------------
  A binary postprocessor with 1 adjustment:

  * Adjust probability threshold to 0.2.

Code
  adjust_equivocal_zone(adjust_probability_threshold(tailor(), 0.2))
Message

  -- tailor ----------------------------------------------------------------------
  A binary postprocessor with 2 adjustments:

  * Adjust probability threshold to 0.2.
  * Add equivocal zone of size 0.1.

error informatively with empty tidyselections

Code
  tailor_fit <- fit(adjust_probability_threshold(tailor(), 0.5),
  two_class_example, outcome = "truth_WRONG", estimate = "predicted",
  probabilities = tidyselect::contains("Class"))
Condition
  Error in `fit()`:
  ! Can't select columns that don't exist.
  x Column `truth_WRONG` doesn't exist.

Code
  tailor_fit <- fit(adjust_probability_threshold(tailor(), 0.5),
  two_class_example, outcome = contains("truth_WRONG"), estimate = "predicted",
  probabilities = tidyselect::contains("Class"))
Condition
  Error in `fit()`:
  ! `outcome` must select at least one column.
  x Selector `contains("truth_WRONG")` did not match any columns in `.data`.

Code
  tailor_fit <- fit(adjust_probability_threshold(tailor(), 0.5),
  two_class_example, outcome = "truth", estimate = "predicted_WRONG",
  probabilities = tidyselect::contains("Class"))
Condition
  Error in `fit()`:
  ! Can't select columns that don't exist.
  x Column `predicted_WRONG` doesn't exist.

Code
  tailor_fit <- fit(adjust_probability_threshold(tailor(), 0.5),
  two_class_example, outcome = "truth", estimate = contains("predicted_WRONG"),
  probabilities = tidyselect::contains("Class"))
Condition
  Error in `fit()`:
  ! `estimate` must select at least one column.
  x Selector `contains("predicted_WRONG")` did not match any columns in `.data`.

Code
  tailor_fit <- fit(adjust_probability_threshold(tailor(), 0.5),
  two_class_example, outcome = contains("truth"), estimate = "predicted",
  probabilities = tidyselect::contains("Class_WRONG"))
Condition
  Error in `fit()`:
  ! `probabilities` must select at least one column.
  x Selector `tidyselect::contains("Class_WRONG")` did not match any columns in `.data`.

Code
  tailor_fit <- fit(adjust_numeric_range(tailor(), 0.5), two_class_example,
  outcome = "Class1", estimate = ".pred", probabilities = tidyselect::contains(
    "Class_WRONG"))
Condition
  Error in `fit()`:
  ! Can't select columns that don't exist.
  x Column `.pred` doesn't exist.