Weighted Youden Index — weighted_youden

This function computes the weighted Youden index for a multi-class prediction model. It assumes that the negative class is the first one.

Usage

weighted_youden_index_vec(
  truth,
  estimate,
  sensitivity_weight = 0.5,
  estimator = NULL,
  na_rm = TRUE,
  case_weights = NULL,
  event_level = "first",
  ...
)

weighted_youden_index(data, ...)

# S3 method for class 'data.frame'
weighted_youden_index(
  data,
  truth,
  estimate,
  sensitivity_weight = 0.5,
  estimator = NULL,
  na_rm = TRUE,
  case_weights = NULL,
  event_level = "first",
  ...
)

Arguments

truth: The column identifier for the true class results (that is a factor).
estimate: The column identifier for the predicted class results (that is also factor).
sensitivity_weight: A scalar value specifying the weight to put on sensitivity. Defaults to 0.5 which puts equal weights to sensitivity and specificity.
estimator: One of: "binary", "macro", "macro_weighted", or "micro" to specify the type of averaging to be done.
na_rm: A logical value indicating whether NA values should be stripped before the computation proceeds.
case_weights: The optional column identifier for case weights.
event_level: A single string. Either "first" or "second" to specify which level of truth to consider as the "event". This argument is only applicable when estimator = "binary".
...: Currently unused.
data: Either a data.frame containing the columns specified by the truth and estimate arguments, or a table/matrix where the true class results should be in the columns of the table.

Value

A scalar storing the value of the weighted Youden index.

Examples

fold1 <- subset(yardstick::hpc_cv, Resample == "Fold01")
weighted_youden_index_vec(fold1$obs, fold1$pred)
#> [1] 0.129896
weighted_youden_index(fold1, obs, pred)
#> # A tibble: 1 × 3
#>   .metric               .estimator .estimate
#>   <chr>                 <chr>          <dbl>
#> 1 weighted_youden_index macro          0.130