Balanced accuracy is mainly used for the imbalanced dataset, where the data label is so imbalanced that the usual Accuracy score is not the perfect evaluator. Think of the case where the model gets 99% accuracy by just saying "no cancer" all the time.

In those cases, we use balanced accuracy.

When to use:

1. highly imbalanced dataset
2. simple, interpretable average recall

References