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Summary

  • Types of outliers
    • global, contextual & collective outliers
  • Outlier detection
    • supervised, semi-supervised, or unsupervised
  • Statistical (or model-based) approaches
  • Proximity-base approaches
  • Clustering-base approaches
  • Classification approaches
  • Mining contextual and collective outliers
  • Outlier detection in high dimensional data


Speaker notes:

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