Systematic Construction of Anomaly Detection Benchmarks from Real Data

@article{Emmott2013SystematicCO,
  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},
  journal={CoRR},
  year={2013},
  volume={abs/1503.01158}
}
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
Highly Cited
This paper has 49 citations. REVIEW CITATIONS

6 Figures & Tables

Topics

Statistics

01020201620172018
Citations per Year

Citation Velocity: 15

Averaging 15 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.