Description Usage Arguments Details Value Examples
Returns the specificity and sensitivity values for a given alpha and beta value.
1 |
alpha |
Type I error or the false positive error |
beta |
Type II error or the false negative error |
Specificity is also known as the true negative rate, which is calculated as the number of true negatives divided by the sum of true negatives and false positives.
Sensitivity is also known as the true positive rate, which is calculated as the number of true positives divided by the sum of true positives and false negatives.
list containing the specificity and sensitivity
1 2 3 |
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