| misclassification_cost {cutpointr} | R Documentation |
Calculate the misclassification cost
Description
Calculate the misclassification cost from
true positives, false positives, true negatives and false negatives.
The inputs must be vectors of equal length.
misclassification_cost = cost_fp * fp + cost_fn * fn
Usage
misclassification_cost(tp, fp, tn, fn, cost_fp = 1, cost_fn = 1, ...)
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. |
cost_fp |
(numeric) the cost of a false positive |
cost_fn |
(numeric) the cost of a false negative |
... |
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(),
npv(),
odds_ratio(),
p_chisquared(),
plr(),
ppv(),
precision(),
prod_ppv_npv(),
prod_sens_spec(),
recall(),
risk_ratio(),
roc01(),
sensitivity(),
specificity(),
sum_ppv_npv(),
sum_sens_spec(),
total_utility(),
tpr(),
tp(),
youden()
Examples
misclassification_cost(10, 5, 20, 10, cost_fp = 1, cost_fn = 5)
misclassification_cost(c(10, 8), c(5, 7), c(20, 12), c(10, 18),
cost_fp = 1, cost_fn = 5)