In
data mining,
anomaly detection (or
outlier detection) is the identification of items, events or observations which do not conform to an expected pattern or other items in a
dataset. Typically the anomalous items will translate to some kind of problem such as
bank fraud, a structural defect, medical problems or errors in a text. Anomalies are also referred to as
outliers, novelties, noise, deviations and exceptions.