arXiv stat.ML
· Papers
Conformal Anomaly Detection in Python: Moving Beyond Heuristic Thresholds with nonconform
arXiv:2605.13642v2 Announce Type: replace Abstract: Most anomaly detection systems output scores rather than calibrated decisions, leaving practitioners to choose thresholds heuristically and without clear statistical interpretation. Conformal anomaly detection addresses this limitation by converting anomaly scores int