AI engineering glossary · Evaluation metrics
What is balanced accuracy?
Balanced accuracy: The average of recall and specificity: (TPR + TNR) / 2. It gives each class equal weight regardless of how many examples it has, so a model cannot look good simply by favouring the majority class. It is a simple fix for accuracy on imbalanced data.
Balanced accuracy: an example
With recall 0.75 and specificity 0.99, balanced accuracy is about 0.87, far below the 98.5% plain accuracy on the same predictions.
Related terms
More Evaluation metrics terms
- BERTScore
- Bits per byte
- BLEU
- Brier score
- Calibration
- Calinski-Harabasz index
- Catalogue coverage
- Character error rate
Where you learn it
Balanced accuracy is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.