False Positive Management

False positives are the tax on anomaly detection. Too many and the team ignores all alerts. Too few and the thresholds are probably too permissive, missing real anomalies. The target false positive rate: less than 20% of alerts should be false positives. Above 20%, alert fatigue sets in. Below 5%, the thresholds may be too conservative. Managing false positives requires a feedback loop: every alert is labeled by the recipient as true positive (real issue) or false positive (not actionable). The labels feed back into the detection system to refine thresholds. Over time, the system learns what matters and what is noise. Without the feedback loop, false positive rates remain static. With it, they improve continuously.