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Generating Artificial Outliers in the Absence of Genuine Ones -- a Survey
Ultimately, to guide the choice of the generation approach in a specific context, we propose an appropriate general-decision process.
Benchmarking Unsupervised Outlier Detection with Realistic Synthetic Data
This allows both for a good coverage of domains and for helpful interpretations of results.
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