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

Field Value
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • ckan
  • geo
  • geoss
  • national
  • north-america
  • united-states
isopen False
license_id us-pd
license_title us-pd
maintainer MARK SCHWABACHER
maintainer_email mark.a.schwabacher@nasa.gov
metadata_created 2025-12-02T10:37:21.618629
metadata_modified 2025-12-02T10:37:21.618633
notes 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/)
num_resources 1
num_tags 8
title Orca