Your question is Explain Core Classification Metrics. 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).
You are reviewing a classification model and the team keeps referring to precision, recall, F1-score, and ROC-AUC. You need to explain what each metric means and when each one matters.
What are precision, recall, F1-score, and ROC-AUC?