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NIPS
2004

Density Level Detection is Classification

9 years 19 days ago
Density Level Detection is Classification
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 results which include consistency and learning rates. Finally, we experimentally compare our SVM with the standard one-class SVM.
Ingo Steinwart, Don R. Hush, Clint Scovel
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where NIPS
Authors Ingo Steinwart, Don R. Hush, Clint Scovel
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