Distance Metric Learning for Conditional Anomaly Detection

Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly detection to the problem of identifying anomalous patterns on a subset of attributes in the data. The anomaly always depends (is conditioned) on the value of remaining attributes. The work presented in this paper focuses on instance

• Type: Conference
• Year: 2008
• Where: FLAIRS
• Authors: Michal Valko, Milos Hauskrecht
• Keywords: Anomaly Detection, Artificial Intelligence, Conditional Anomaly Detection, Detection Methods, FLAIRS 2008