cal_confus: Calculate confusion matrices

In multiROC: Calculating and Visualizing ROC and PR Curves Across Multi-Class Classifications

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 true_vec
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)

Example output

multiROC documentation built on May 1, 2019, 10:11 p.m.