Systematic Construction of Anomaly Detection Benchmarks from Real Data

  title={Systematic Construction of Anomaly Detection Benchmarks from Real Data},
  author={Andrew Emmott and Shubhomoy Das and Thomas G. Dietterich and Alan Fern and Weng-Keen Wong},
Research in anomaly detection suffers from a lack of realistic and publicly-available problem sets. This paper discusses what properties such problem sets should possess. It then introduces a methodology for transforming existing classification data sets into ground-truthed benchmark data sets for anomaly detection. The methodology produces data sets that vary along three important dimensions: (a) point difficulty, (b) relative frequency of anomalies, and (c) clusteredness. We apply our… CONTINUE READING
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