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Outlier Detection (1): Statistical Methods

  • Statistical methods (also known as model-based methods) assume that the normal data follow some statistical model (a stochastic model)
    • The data not following the model are outliers.
  • Effectiveness of statistical methods: highly depends on whether the assumption of statistical model holds in the real data
  • There are rich alternatives to use various statistical models
    • E.g., parametric vs. non-parametric
  • Example (below figure): First use Gaussian distribution to model the normal data
    • For each object y in region R, estimate gD(y), the probability of y fits the Gaussian distribution
    • If gD(y) is very low, y is unlikely generated by the Gaussian model, thus an outlier

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