English

OutlierDetection.jl: A modular outlier detection ecosystem for the Julia programming language

Machine Learning 2022-11-10 v1

Abstract

OutlierDetection.jl is an open-source ecosystem for outlier detection in Julia. It provides a range of high-performance outlier detection algorithms implemented directly in Julia. In contrast to previous packages, our ecosystem enables the development highly-scalable outlier detection algorithms using a high-level programming language. Additionally, it provides a standardized, yet flexible, interface for future outlier detection algorithms and allows for model composition unseen in previous packages. Best practices such as unit testing, continuous integration, and code coverage reporting are enforced across the ecosystem. The most recent version of OutlierDetection.jl is available at https://github.com/OutlierDetectionJL/OutlierDetection.jl.

Keywords

Cite

@article{arxiv.2211.04550,
  title  = {OutlierDetection.jl: A modular outlier detection ecosystem for the Julia programming language},
  author = {David Muhr and Michael Affenzeller and Anthony D. Blaom},
  journal= {arXiv preprint arXiv:2211.04550},
  year   = {2022}
}

Comments

5 pages, 5 figures

R2 v1 2026-06-28T05:27:30.178Z