Data Mining pp 265-283 | Cite as

Outlier Analysis: Advanced Concepts

  • Charu C. AggarwalEmail author


Many scenarios for outlier analysis cannot be addressed with the use of the techniques discussed in the previous chapter. For example, the data type has a critical impact on the outlier detection algorithm. In order to use an outlier detection algorithm on categorical data, it may be necessary to change the distance function or the family of distributions used in expectation–maximization (EM) algorithms. In many cases, these changes are exactly analogous to those required in the context of the clustering problem.


Outlier Detection Combination Function Outlier Analysis Random Subspace Sparsity Coefficient 
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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.IBM T.J. Watson Research CenterYorktown HeightsUSA

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