Your question is Evaluating Beyond Accuracy. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How do you evaluate the performance of a model beyond simple accuracy?
Discuss how you would select appropriate metrics, validate performance, analyze errors, and assess whether predictions are useful for the intended application. Address how class imbalance, probability calibration, decision thresholds, and business costs can change the evaluation approach.