The stray algorithm detects anomalies and micro-clusters in high-dimensional data using the k-nearest-neighbor distance with the maximum gap, with an extreme-value-theory threshold, and outperforms HDoutliers on the illustrated cases.
The anomalous threshold calculation in Schwarz (2008); Burridge & Taylor (2006) and Wilkinson (2017) is an application of Weissman’s spacing theorem (Weissman
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Anomaly Detection in High Dimensional Data
The stray algorithm detects anomalies and micro-clusters in high-dimensional data using the k-nearest-neighbor distance with the maximum gap, with an extreme-value-theory threshold, and outperforms HDoutliers on the illustrated cases.