What is balanced accuracy?
easyAnswer
- Balanced accuracy = (sensitivity + specificity) / 2 for binary, or the macro average of per-class recall for multi-class.
- It corrects accuracy by treating every class equally regardless of size — a 50% baseline for random guessing on any class balance.
- Handy single-number summary for imbalanced classification; equivalent to accuracy on perfectly balanced data.
- Doesn't use precision, so pair it with PR-AUC when the positive class is what you care about.
Check yourself — multiple choice
- Same as accuracy
- Average of per-class recall; corrects accuracy for imbalance
- Only defined for regression
- Product of precision and recall
Balanced accuracy = macro recall. Corrects accuracy for class imbalance.
#metrics#classification#imbalance
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