[!!!] Performance measures

Source: R/roc_performance_measures.R

Calculate various performance measures for classificatory analysis
[!!!] (...The description is incomplete...)

calculate_acc(TP, FN, FP, TN)

roc_calculate_acc(obj)

calculate_bac(SE, SP)

roc_calculate_bac(obj)

calculate_auc(SE, SP)

roc_calculate_auc(obj)

calculate_npv(TN, FN)

roc_calculate_npv(obj)

calculate_ppv(TP, FP)

roc_calculate_ppv(obj)

calculate_sensitivity(TP, FN)

roc_calculate_se(obj)

calculate_specificity(TN, FP)

roc_calculate_sp(obj)

calculate_youdens_j(SE, SP)

roc_youdens_j(obj)

calculate_kappa(TP, FN, FP, TN)

roc_calculate_kappa(obj)

calculate_wkappa(TP, FN, FP, TN)

roc_calculate_wkappa(obj)

Arguments

TP

(numeric) Number of true positives.
FN

(numeric) Number of false negatives.
FP

(numeric) Number of false positives.
TN

(numeric) Number of true negatives.
obj

Either an roc_result_list or an roc_results object.
SE

(numeric) Vector of sensitivities.
SP

(numeric) Vector of specificities

See also

Other functions for ROC: access_elements, calculate_performance(), print.as_str(), roc_predict()

Author

Vilmantas Gegzna