tabularfamily
PyOD
Python library of anomaly and outlier detection algorithms (60 or more detectors per its repository) for tabular, time series, graph and other data. Paper by Zhao et al. (2019).
Levelfamily
Classtabular
Parametersnot in the notes
Contextnot in the notes
Released6 Jan 2019
Opennessopen source
Runs onnot in the notes
Statusactive
Identity
- Developer
- Carnegie Mellon University
- Family
- not in the notes
- Released
- 6 Jan 2019 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- other Python library of outlier detectors
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- table
- Output
- table
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- open source
- Licence
- not in the notes sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- Repository licence BSD-2-Clause (GitHub API); no AURION licence record exists for it yet.
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
ModelPyODCarnegie Mellon University, tabular
PyODCarnegie Mellon University, tabularUse CasesFraud DetectionFinanceAML Transaction Monitoring and Suspicious Account DetectionFinanceUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
OVOIn production, 25 Jun 2026
Kementerian Komunikasi dan Digital (Komdigi)Planned, 13 Apr 2026
PT Jalin Pembayaran NusantaraPlanned, 22 Oct 2025
Bank Negara Indonesia (BNI)In production, 7 Aug 2025+3 moreDeployments of these use cases; none names this model.
OVOIn production, 25 Jun 2026Kementerian Komunikasi dan Digital (Komdigi)Planned, 13 Apr 2026PT Jalin Pembayaran NusantaraPlanned, 22 Oct 2025Bank Negara Indonesia (BNI)In production, 7 Aug 2025+3 moreDeployments of these use cases; none names this model.Organisations 1
Sources
- arxiv.org/abs/1901.01588 https://arxiv.org/abs/1901.01588
- github.com/yzhao062/pyod https://github.com/yzhao062/pyod
- pyod.readthedocs.io/en/latest https://pyod.readthedocs.io/en/latest/
- arxiv.org/html/1901.01588 https://arxiv.org/html/1901.01588
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "PyOD", https://aurion.semai.id/models/pyod/, records of October 2026.