A data scientist uses the Matthews Correlation Coefficient (MCC) instead of accuracy on an extremely imbalanced dataset where 98% of records are class 0. What is the key advantage of MCC in this situation?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because MCC incorporates TP, TN, FP, and FN symmetrically. A model predicting only the majority class gets MCC ≈ 0, exposing its uselessness despite high accuracy.
Full explanation below image
Full Explanation
B is correct because MCC incorporates TP, TN, FP, and FN symmetrically. A model predicting only the majority class gets MCC ≈ 0, exposing its uselessness despite high accuracy. A is wrong; MCC ranges from -1 to +1, not 0 to 1. C is wrong; MCC and macro F1 are mathematically different metrics. D is wrong; MCC is computed at a specific threshold from the confusion matrix.