Chapter

Outlier Analysis

pp 1-34

Date:

An Introduction to Outlier Analysis

  • Charu C. AggarwalAffiliated withIBM T.J. Watson Research Center

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Abstract

Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data mining and statistics literature. In most applications, the data is created by one or more generating processes, which could either reflect activity in the system or observations collected about entities. When the generating process behaves unusually, it results in the creation of outliers. Therefore, an outlier often contains useful information about abnormal characteristics of the systems and entities that impact the data generation process. The recognition of such unusual characteristics provides useful application-specific insights.