Outlier and anomaly detection

Anomalies are the unusual and unexpected patterns in an observed world. Thus analyzing, identifying, understanding, and predicting anomalies from seen and unseen data is one of the most important task in data mining. Therefore, detecting anomalies allows extracting critical information from data which then can be used for numerous applications.

While anomaly is a generally accepted term, other synonyms, such as outliers, discordant observations, exceptions, aberrations, surprises, peculiarities or contaminants, are often used in different application domains. In particular, anomalies and outliers are often used interchangeably. Anomaly detection finds extensive use in fraud detection for credit cards, insurance or health care, intrusion detection for cyber-security, fault detection in safety critical systems, and military surveillance for enemy activities.

The importance of anomaly detection stems from the fact that for a variety of application domains anomalies...