Probabilistic and Statistical Models for Outlier Detection

  • Charu C. Aggarwal
Chapter

Abstract

The earliest methods for outlier detection were rooted in probabilistic and statistical models and date back to the nineteenth century [180]. These methods were proposed well before the advent and popularization of computer technology and were therefore designed without much focus on practical issues 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.

Keywords

Convex Hull Gaussian Mixture Model Mahalanobis Distance Mixture Component Outlier Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Charu C. Aggarwal
    • 1
  1. 1.IBM T.J. Watson Research CenterNew YorkUSA

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