Orca
Orca is a data-driven, unsupervised anomaly detection algorithm that uses a distance-based approach. It uses a novel pruning rule that allows it to run in nearly linear time. Orca was co-developed by Stephen Bay of ISLE and Mark Schwabacher of NASA ARC. More information about Orca, including downloadable software, can be found here:
[http://stephenbay.net/orca/](http://stephenbay.net/orca/)
A conference paper about Orca can be found here:
[https://dashlink.arc.nasa.gov/paper/mining-distance-based-outliers-in-near-linear-time/](https://dashlink.arc.nasa.gov/paper/mining-distance-based-outliers-in-near-linear-time/)
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode |
[ "026:00" ] |
| contactPoint |
{ "fn": "MARK SCHWABACHER", "@type": "vcard:Contact", "hasEmail": "mailto:mark.a.schwabacher@nasa.gov" } |
| description | Orca is a data-driven, unsupervised anomaly detection algorithm that uses a distance-based approach. It uses a novel pruning rule that allows it to run in nearly linear time. Orca was co-developed by Stephen Bay of ISLE and Mark Schwabacher of NASA ARC. More information about Orca, including downloadable software, can be found here: [http://stephenbay.net/orca/](http://stephenbay.net/orca/) A conference paper about Orca can be found here: [https://dashlink.arc.nasa.gov/paper/mining-distance-based-outliers-in-near-linear-time/](https://dashlink.arc.nasa.gov/paper/mining-distance-based-outliers-in-near-linear-time/) |
| identifier | DASHLINK_121 |
| issued | 2010-09-10 |
| keyword |
[ "ames", "dashlink", "nasa" ] |
| landingPage | https://c3.nasa.gov/dashlink/resources/121/ |
| modified | 2025-07-17 |
| programCode |
[ "026:029" ] |
| publisher |
{ "name": "Dashlink", "@type": "org:Organization" } |
| title | Orca |
