Systematic Construction of Anomaly Detection Benchmarks from Real Data

Abstract

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… (More)
DOI: 10.1145/2500853.2500858
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@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} }