Data science team must offline-evaluate a classifier that labels videos as harmful.

What offline evaluation framework would you use? Detail suitable metrics (e.g., precision, recall, PR-AUC), handling class imbalance, ground-truth collection, threshold selection based on business costs, and potential fairness checks.

Discuss label skew, cost of false positives vs negatives, and calibration.

Meta Data Scientist interview question: Evaluate Classifier with Precision, Recall, and Fairness Metrics. {"blocks": [{"key": "05b82e18", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {...