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

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Probabilistic and Statistical Models for Outlier Detection,s such as data representation or computational efficiency. Nevertheless, the underlying mathematical models are extremely useful and have eventually been adapted to a variety of computational scenarios.

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Outlier Ensembles,ard because of its ability to combine the outputs of multiple algorithms. In this chapter, will use the terms . and . interchangeably to denote the individual algorithms whose outputs are combined to create the final result.

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Applications of Outlier Analysis,arious techniques discussed in earlier chapters. The practical issues and challenges in the context of real data sets will also be discussed. This will provide a broader understanding of the issues involved in ..

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ights into when and why particular algorithms work effectiveThis book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appe

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