Calculate a confusion matrix

Usage

confusion_matrix(
  observed,
  predicted,
  label_false = "FALSE",
  label_true = "TRUE"
)

# S3 method for class 'confusionmatrix'
as.data.frame(x, row.names = NULL, optional = FALSE, digits = 2, ...)

# S3 method for class 'confusionmatrix'
print(x, digits = 2, ...)

Arguments

observed: vector of observed values. The vector should either be a numeric vector of 0s and 1s or logical.
predicted: vector of predicted values. The vector should either be a numeric vector of 0s and 1s or logical.
label_false: label for FALSE values
label_true: label for TRUE values.
x: the result of [confusion_matrix()].
row.names: not used.
optional: not used.
digits: number of decimal places to print.
...: currently not used.

Value

a data.frame of the confusion matrix.

Examples

observed <- c(rep(FALSE, 10), rep(TRUE, 2))
predicted <- rep(TRUE, 12)
confusion_matrix(observed, predicted, label_true = 'Success', label_false = 'Failure')
#>            predicted            
#>   observed   Failure     Success
#>    Failure 0 (0.00%) 10 (83.33%)
#>    Success 0 (0.00%)  2 (16.67%)
#> Accuracy: 16.67%
#> Sensitivity: %
#> Specificity: %