Compute a confusion matrix for categorical or binary predictions
Usage
confusion_matrix(truth, predicted, levels = NULL)
Arguments
- truth
factor or character vector of true classes.
- predicted
factor or character vector of predicted classes.
- levels
character vector of class levels (default: union of
truth and predicted levels).
Value
A list with:
- table
Confusion matrix (rows = truth, columns = predicted).
- accuracy
Overall accuracy.
- per_class
Data.frame with per-class precision, recall, F1.
Examples
confusion_matrix(
truth = c("a", "a", "b", "b"),
predicted = c("a", "b", "b", "b")
)
#> $table
#> Predicted
#> Truth a b
#> a 1 1
#> b 0 2
#>
#> $accuracy
#> [1] 0.75
#>
#> $per_class
#> class tp precision recall f1
#> 1 a 1 1.0000000 0.5 0.6666667
#> 2 b 2 0.6666667 1.0 0.8000000
#>
