Matthews Correlation Coefficient (MCC)

INFO

Evaluates classification models on imbalanced datasets by considering all confusion matrix elements.

How It Works

Matthews Correlation Coefficient (MCC):

$$\text{MCC}=\frac{TP\cdot TN-FP\cdot FN}{\sqrt{(TP+FP)(TP+FN)(TN+FP)(TN+FN)}}$$

• TP: True Positives
• TN: True Negatives
• FP: False Positives
• FN: False Negatives

What to Look For

• Range: -1 (total disagreement) to +1 (perfect prediction)
• Robust metric for imbalanced datasets
• Preferred when accuracy is misleading

Application Models

• Logistic Regression
• Random Forest Classification
• Support Vector Machine (SVM)