A fraud-detection model produced the following confusion matrix after scoring 10 000 transactions:
| Actual Fraud | Actual Legit | |
|---|---|---|
| Pred Fraud | 240 | 160 |
| Pred Legit | 60 | 9 540 |
Using these counts, what is the Matthews Correlation Coefficient (MCC)? Round your answer to two decimal places.
0.44
0.68
0.80
0.26
The MCC is a balanced measure that combines all four cells of the confusion matrix:
MCC = (TP × TN - FP × FN) / √[(TP+FP)(TP+FN)(TN+FP)(TN+FN)]
Substituting the values TP = 240, TN = 9 540, FP = 160, FN = 60:
Numerator = (240 × 9 540) - (160 × 60) = 2 280 000 Denominator = √[(240+160)(240+60)(9 540+160)(9 540+60)] = √[400 × 300 × 9 700 × 9 600] ≈ 3 342 813.19
MCC ≈ 2 280 000 / 3 342 813.19 ≈ 0.68
Therefore 0.68 (to two decimal places) is correct, while the other options either omit one of the error terms or confuse MCC with recall, precision, or F1, yielding values around 0.80, 0.60, or below 0.50.
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