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)

[Package cutpointr version 1.1.1 Index]