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/

A conference paper about Orca can be found here:

https://dashlink.arc.nasa.gov/paper/mining-distance-based-outliers-in-near-linear-time/

Data and Resources

This dataset has no data

Additional Info

Field	Value
Maintainer	MARK SCHWABACHER
Last Updated	March 31, 2025, 21:22 (UTC)
Created	March 31, 2025, 21:22 (UTC)
accessLevel	public
accrualPeriodicity	irregular
bureauCode	{026:00}
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catalog_@id	https://data.nasa.gov/data.json
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harvest_object_id	32e24778-1a3e-4bb4-9e82-817378380296
harvest_source_id	61638e72-b36c-4866-9d28-551a3062f158
harvest_source_title	DNG Legacy Data
identifier	DASHLINK_121
issued	2010-09-10
landingPage	https://c3.nasa.gov/dashlink/resources/121/
modified	2020-01-29
programCode	{026:029}
publisher	Dashlink
resource-type	Dataset
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