The optimal threshold depends on the specific problem and the desired trade-off between different types of errors:
- Manual Selection: Based on domain expertise or prior knowledge, choose a threshold that seems reasonable.
- Receiver Operating Characteristic (ROC (Receiver Operating Characteristic)) Curve Analysis: Plot the true positive rate (TPR) against the false positive rate (FPR) for different threshold values. The optimal threshold often lies near the “elbow” of the ROC curve, where a small increase in FPR results in a significant increase in TPR.
- Precision-Recall Curve Analysis: Plot the precision against the recall for different threshold values. The optimal threshold often lies near the “elbow” of the precision-recall curve, where a small decrease in precision results in a significant increase in recall.
- Cost-Sensitive Analysis: Assign different costs to different types of errors (e.g., false positives vs. false negatives) and choose the threshold that minimizes the total cost.