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/)
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 |
