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Anomaly detection is the identification of data points, items, observations or events that do not conform to the expected pattern of a given group. These anomalies occur very infrequently but may signify a large and significant threat such as cyber intrusions or fraud.
Anomaly detection is heavily used in behavioral analysis and other forms of analysis in order to aid in learning about the detection, identification and prediction of the occurrence of these anomalies.
Anomaly detection is also known as outlier detection.