52Implement a precision-recall (or ROC) curve and AUC from scores and labels.▼mediumAmazonGoogleMeta2 replies◆ premiumBuilding a PR/ROC curve from scratch proves you understand thresholds and the precision/recall tradeoff. The real signal is sweeping the threshold in one sorted pass and integrating the area. Here is the implementation.Open full answer →
83Your classifier outputs probabilities, but you need a decision. How do you pick the threshold (it's rarely 0.5)?▼mediumAmazonStripeMeta1 replies◆ premiumDefaulting to 0.5 is leaving money or safety on the table. The right cutoff comes from the cost of each error and the operating constraint, not the model. Here is how to set it deliberately.Open full answer →
