Density Level Detection is Classification
Ingo Steinwart, Don R. Hush, Clint Scovel · 2004
We show that anomaly detection can be interpreted as a binary classifi-cation problem. Using this interpretation we propose a support vector machine (SVM) for anomaly detection. We then present some theoret-ical results which include consistency and learning rates. Finally, we experimentally compare our SVM with the standard one-class SVM. 1