Data Mining

pp 265-283


Outlier Analysis: Advanced Concepts

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

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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.