precision: Calculate precision

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

Calculate precision

Description

Calculate precision (equal to the positive predictive value) from true positives, false positives, true negatives and false negatives. The inputs must be vectors of equal length.

precision = tp / (tp + fp)

Usage

precision(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(), prod_ppv_npv(), prod_sens_spec(), recall(), risk_ratio(), roc01(), sensitivity(), specificity(), sum_ppv_npv(), sum_sens_spec(), total_utility(), tpr(), tp(), youden()

Examples

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

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