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PyNomaly: Anomaly detection using Local Outlier Probabilities (LoOP).

Research article (The Journal of Open Source Software, 2018) · cited 17× · AI/ML
academia openalex:W2898322594
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PyNomaly: Anomaly detection using Local Outlier Probabilities (LoOP).

Summary

PyNomaly: Anomaly detection using Local Outlier Probabilities (LoOP). is a scholarly article[1].

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  • PyNomaly: Anomaly detection using Local Outlier Probabilities (LoOP).'s instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). PyNomaly: Anomaly detection using Local Outlier Probabilities (LoOP).. Retrieved May 24, 2026, from https://4ort.xyz/entity/pynomaly-anomaly-detection-using-local-outlier-probabilities-loop
MLA “PyNomaly: Anomaly detection using Local Outlier Probabilities (LoOP)..” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/pynomaly-anomaly-detection-using-local-outlier-probabilities-loop.
BibTeX @misc{4ortxyz_pynomaly-anomaly-detection-using-local-outlier-probabilities-loop_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{PyNomaly: Anomaly detection using Local Outlier Probabilities (LoOP).}}, year = {2026}, url = {https://4ort.xyz/entity/pynomaly-anomaly-detection-using-local-outlier-probabilities-loop}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): PyNomaly: Anomaly detection using Local Outlier Probabilities (LoOP). — https://4ort.xyz/entity/pynomaly-anomaly-detection-using-local-outlier-probabilities-loop (retrieved 2026-05-24)

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