It is the point on the ROC curve where the False Positive Rate equals the False Negative Rate. The Bayes classifier will operate at the EER point when:
- Equal Priors When the prior probabilities are equal, the Bayes decision rule simplifies to comparing only the likelihoods. This creates a balanced starting point for classification.
- Cost of mis-classification is equal If the cost of a false positive equals the cost of a false negative, the Bayes classifier won’t be biased towards minimizing one type of error over the other.
Applications of the having the Operating Condition on the Right side of the EER Curve
- Medical screening tests for serious diseases: It’s often preferable to have more false positives (which can be ruled out with further testing) than to miss actual cases of a dangerous disease.
- Fraud detection in financial transactions: Banks may prefer to flag more transactions as potentially fraudulent for review, even if some are legitimate, rather than miss actual fraud attempts.