cal_confus {multiROC} | R Documentation |
Calculate confusion matrices
Description
This function calculates the confusion matrices across different cutoff points.
Usage
cal_confus(true_vec, pred_vec, force_diag=TRUE)
Arguments
true_vec |
A binary vector of real labels |
pred_vec |
A continuous predicted score(probabilities) vector, must be the same length with |
force_diag |
If TRUE, TPR and FPR will be forced to across (0, 0) and (1, 1) |
Details
This function calculates the TP, FP, FN, TN, TPR, FPR and PPV across different cutoff points of pred_vec
. TPR and FPR are forced to across (0, 0) and (1, 1) if force_diag=TRUE
.
Value
TP |
True positive |
FP |
False positive |
FN |
False negative |
TN |
True negative |
TPR |
True positive rate |
FPR |
False positive rate |
PPV |
Positive predictive value |
References
https://en.wikipedia.org/wiki/Confusion_matrix
Examples
data(test_data)
true_vec <- test_data[, 1]
pred_vec <- test_data[, 5]
confus_res <- cal_confus(true_vec, pred_vec)
[Package multiROC version 1.1.1 Index]