You are discussing how to evaluate an AI model before launch and after deployment. The team wants a clear way to measure performance, but the right metric depends on the task and the cost of different mistakes.
What metrics would you use to evaluate the performance of an AI model?
When accuracy is useful and when it is misleadingHow precision and recall reflect different error costsWhy F1 score is helpful for imbalanced classificationHow AUC-ROC evaluates ranking quality across thresholds