Abstract
PyGOD is an open-source Python library for detecting outliers in graph data. As the first comprehensive library of its kind, PyGOD supports a wide array of leading graph-based methods for outlier detection under an easy-to-use, well-documented API designed for use by both researchers and practitioners. PyGOD provides modularized components of the different detectors implemented so that users can easily customize each detector for their purposes. To ease the construction of detection workflows, PyGOD offers numerous commonly used utility functions. To scale computation to large graphs, PyGOD supports functionalities for deep models such as sampling and mini-batch processing. PyGOD uses best practices in fostering code reliability and maintainability, including unit testing, continuous integration, and code coverage.
| Original language | English |
|---|---|
| Journal | Journal of Machine Learning Research |
| Volume | 25 |
| State | Published - 2024 |
| Externally published | Yes |
Keywords
- anomaly detection
- graph learning
- graph neural networks
- outlier detection
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