Density Level Detection is Classification
Steinwart, Ingo, Hush, Don, Scovel, Clint
–Neural Information Processing Systems
We show that anomaly detection can be interpreted as a binary classification problem.Using this interpretation we propose a support vector machine (SVM) for anomaly detection. We then present some theoretical resultswhich include consistency and learning rates. Finally, we experimentally compare our SVM with the standard one-class SVM.
Neural Information Processing Systems
Dec-31-2005