metrics.md
In yardstick: Tidy Characterizations of Model Performance

bad args

Code
  metrics(two_class_example, truth, Class1)
Condition
  Error in `metric_set()`:
  ! Failed to compute `accuracy()`.
  Caused by error:
  ! `estimate` should be a factor, not a `numeric`.

Code
  metrics(two_class_example, Class1, truth)
Condition
  Error in `metric_set()`:
  ! Failed to compute `rmse()`.
  Caused by error:
  ! `estimate` should be a numeric, not a `factor`.

Code
  metrics(three_class, "obs", "pred", setosa, versicolor)
Condition
  Error in `mn_log_loss()`:
  ! The number of levels in `truth` (3) must match the number of columns supplied in `...` (2).

metrics() - `options` is deprecated

Code
  out <- metrics(two_class_example, truth, predicted, Class1, options = 1)
Condition
  Warning:
  The `options` argument of `metrics()` was deprecated in yardstick 1.0.0.
  i This argument no longer has any effect, and is being ignored. Use the pROC package directly if you need these features.

numeric metric sets

Code
  metric_set(rmse, "x")
Condition
  Error:
  ! All inputs to `metric_set()` must be functions. These inputs are not: (2).

mixing bad metric sets

Code
  metric_set(rmse, accuracy)
Condition
  Error in `validate_function_class()`:
  ! 
  The combination of metric functions must be:
  - only numeric metrics
  - a mix of class metrics and class probability metrics

  - a mix of dynamic and static survival metrics

  The following metric function types are being mixed:
  - numeric (rmse)
  - class (accuracy)

print metric_set works

Code
  metric_set(rmse, rsq, ccc)
Output
  # A tibble: 3 x 3
    metric class          direction
    <chr>  <chr>          <chr>    
  1 rmse   numeric_metric minimize 
  2 rsq    numeric_metric maximize 
  3 ccc    numeric_metric maximize

`metric_set()` errors contain env name for unknown functions (#128)

Code
  metric_set(accuracy, foobar, sens, rlang::abort)
Condition
  Error in `validate_function_class()`:
  ! 
  The combination of metric functions must be:
  - only numeric metrics
  - a mix of class metrics and class probability metrics

  - a mix of dynamic and static survival metrics

  The following metric function types are being mixed:
  - class (accuracy, sens)
  - other (foobar <test>, abort <namespace:rlang>)

Code
  metric_set(accuracy, foobar, sens, rlang::abort)
Condition
  Error in `validate_function_class()`:
  ! 
  The combination of metric functions must be:
  - only numeric metrics
  - a mix of class metrics and class probability metrics

  - a mix of dynamic and static survival metrics

  The following metric function types are being mixed:
  - class (accuracy, sens)
  - other (foobar <test>, abort <namespace:rlang>)

`metric_set()` gives an informative error for a single non-metric function (#181)

Code
  metric_set(foobar)
Condition
  Error in `validate_function_class()`:
  ! 
  The combination of metric functions must be:
  - only numeric metrics
  - a mix of class metrics and class probability metrics

  - a mix of dynamic and static survival metrics

  The following metric function types are being mixed:
  - other (foobar <test>)

propagates 'caused by' error message when specifying the wrong column name

Code
  set(two_class_example, truth, Class1, estimate = predicted, case_weights = weight)
Condition
  Error in `metric_set()`:
  ! Failed to compute `accuracy()`.
  Caused by error:
  ! Can't subset columns that don't exist.
  x Column `weight` doesn't exist.