Balanced accuracy
The arithmetic mean of the recall of each class, suitable for binary classification evaluation where the proportions of positive and negative samples are imbalanced.
Timeline (last 90 days)
Balanced accuracy is the arithmetic mean of the recall rates of each class, suitable for binary classification evaluation with imbalanced positive and negative sample proportions.
Balanced accuracy is calculated as the arithmetic mean of per-class recall rates and is used to address class imbalance problems.
The experiment used balanced accuracy as the evaluation metric, covering 8 classification datasets.
Balanced accuracy equals the arithmetic mean of the recall rates of each category and is used to correct for multi-class imbalance issues.
All Facts (4)
Balanced accuracy is the arithmetic mean of the recall rates of each class, suitable for binary classification evaluation with imbalanced positive and negative sample proportions.
50%UnverifiedBalanced accuracy is calculated as the arithmetic mean of per-class recall rates and is used to address class imbalance problems.
50%UnverifiedThe experiment used balanced accuracy as the evaluation metric, covering 8 classification datasets.
50%UnverifiedBalanced accuracy equals the arithmetic mean of the recall rates of each category and is used to correct for multi-class imbalance issues.
50%