robMCC: Robust Matthews correlation coefficient

In RobustMetrics: Calculates Robust Performance Metrics for Imbalanced Classification Problems

Robust Matthews correlation coefficient

Description

Compute a robust version of Matthews correlation coefficient (MCC).

Usage

robMCC(
  actual = NULL,
  predicted = NULL,
  TP = NULL,
  FN = NULL,
  FP = NULL,
  TN = NULL,
  d = 0.1
)

Arguments

actual	A vector of actual values (1/0 or TRUE/FALSE)
predicted	A vector of prediction values (1/0 or TRUE/FALSE)
TP	Count of true positives (correctly predicted 1/TRUE)
FN	Count of false negatives (predicted 0/FALSE, but actually 1/TRUE)
FP	Count of false positives (predicted 1/TRUE, but actually 0/FALSE)
TN	Count of true negatives (correctly predicted 0/FALSE)
d	Parameter of the robust MCC

Details

Calculate the robust MCC. Provide either:

• actual and predicted or

• TP, FN, FP and TN.

If d=0, the robust MCC coincides with the MCC.

Value

robust MCC.

References

Holzmann, H., Klar, B. (2026). Robust performance metrics for imbalanced classification problems. arXiv:2404.07661. LINK

Examples

actual <- c(1,1,1,1,1,1,0,0,0,0)
predicted <- c(1,1,1,1,0,0,1,0,0,0)
robMCC(actual, predicted, d=0.05)
robMCC(TP=4, FN=2, FP=1, TN=3, d=0.05)

RobustMetrics documentation built on Aug. 21, 2026, 5:17 p.m.