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Probabilistic and Statistical Models for Outlier Detection

  • Charu C. Aggarwal
Chapter

Abstract

The oldest methods for outlier detection are rooted in probabilistic and statistical models, and date back to the nineteenth century [149]. The earliest methods were proposed well before the advent and popularization of computer technology. Therefore, these methods were 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 Central Limit Theorem Gaussian Mixture Model Mahalanobis Distance 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 Science+Business Media New York 2013

Authors and Affiliations

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

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