Titlebook: Outlier Analysis; Charu C. Aggarwal Textbook 2017Latest edition Springer International Publishing AG 2017 Outlier Analysis.Anomaly detecti

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Proximity-Based Outlier Detection,Proximity-based techniques define a data point as an outlier when its locality (or .) is sparsely populated. The proximity of a data point may be defined in a variety of ways, which are subtly different from one another but are similar enough to merit unified treatment within a single chapter.

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Supervised Outlier Detection,ases, different types of abnormal instances could be present, and it may be desirable to distinguish among them. For example, in an intrusion-detection scenario, different types of intrusion anomalies are possible, and the specific type of an intrusion is important information.

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Outlier Detection in Categorical, Text, and Mixed Attribute Data,rently categorical. In many cases, categorical and numeric attributes are found in the same data set. Such . are often challenging to machine-learning applications because of the difficulties in treating the various types of attributes in a homogeneous and consistent way.

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