| roc01 {cutpointr} | R Documentation |
Calculate the distance between points on the ROC curve and (0,1)
Description
Calculate the distance on the ROC space between points on the ROC curve
and the point of perfect discrimination
from true positives, false positives, true negatives and false negatives.
The inputs must be vectors of equal length. To be used with
method = minimize_metric.
sensitivity = tp / (tp + fn)
specificity = tn / (tn + fp)
roc01 = sqrt((1 - sensitivity)^2 + (1 - specificity)^2)
Usage
roc01(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(),
prod_sens_spec(),
recall(),
risk_ratio(),
sensitivity(),
specificity(),
sum_ppv_npv(),
sum_sens_spec(),
total_utility(),
tpr(),
tp(),
youden()
Examples
roc01(10, 5, 20, 10)
roc01(c(10, 8), c(5, 7), c(20, 12), c(10, 18))
oc <- cutpointr(suicide, dsi, suicide,
method = minimize_metric, metric = roc01)
plot_roc(oc)