OutlierDetection.jl: A modular outlier detection ecosystem for the Julia programming language
This work addresses the need for a modular and efficient outlier detection framework for Julia users, though it is incremental as it builds on existing outlier detection concepts in a new programming environment.
The authors tackled the lack of a comprehensive outlier detection ecosystem in Julia by developing OutlierDetection.jl, which provides high-performance algorithms, a standardized interface, and model composition capabilities, resulting in an open-source package that supports scalable outlier detection.
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.