RobustMetrics (version 0.1.1)

robMCC: 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
)

Value

robust MCC.

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.

References

Holzmann, H., Klar, B. (2024). 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)