prod_sens_spec: Calculate the product of sensitivity and specificity

In cutpointr: Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks

Calculate the product of sensitivity and specificity

Description

Calculate the product of sensitivity and specificity from true positives, false positives, true negatives and false negatives. The inputs must be vectors of equal length.

sensitivity = tp / (tp + fn)
specificity = tn / (tn + fp)
prod_sens_spec = sensitivity * specificity

Usage

prod_sens_spec(tp, fp, tn, fn, ...)

Arguments

tp	(numeric) number of true positives.
fp	(numeric) number of false positives.
tn	(numeric) number of true negatives.
fn	(numeric) number of false negatives.
...	for capturing additional arguments passed by method.

See Also

Other metric functions: F1_score(), Jaccard(), abs_d_ppv_npv(), abs_d_sens_spec(), accuracy(), cohens_kappa(), cutpoint(), false_omission_rate(), metric_constrain(), misclassification_cost(), npv(), odds_ratio(), p_chisquared(), plr(), ppv(), precision(), prod_ppv_npv(), recall(), risk_ratio(), roc01(), sensitivity(), specificity(), sum_ppv_npv(), sum_sens_spec(), total_utility(), tpr(), tp(), youden()

Examples

prod_sens_spec(10, 5, 20, 10)
prod_sens_spec(c(10, 8), c(5, 7), c(20, 12), c(10, 18))

cutpointr documentation built on April 14, 2022, 1:06 a.m.