A statistical framework for graph anomaly detection
Project description
SFGAD is a tool for detecting anomalies in graph and graph streams with python.
I provides:
- Efficient computation of graph features
- Statistical models for detecting anomalous behavior
- Graph scanning to detect connected graph anomalies
- A customizable detection framework with 6 components
- Several pre-defined configurations
Process
Installation
Dependencies
- Python: 3.5 or higher
- NumPy: 1.8.2 or higher
- SciPy: 0.13.3 or higher
- Pandas: 0.22.0 or higher
- NetworkX: 1.11.0 or higher
Installation (coming soon)
Installation of the latest release is available at the Python package index and on conda.
conda install sfgad
or
pip install sfgad
The source code is currently available on GitHub: https://github.com/sudrich/sf-gad
Testing
For testing use pytest from the source directory:
pytest sfgad
Acknowledgements
This work originated from the QuestMiner project (grant no. 01IS12051) and was partially funded by the German Federal Ministry of Education and Research (BMBF).
Release history Release notifications
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
| Filename, size | File type | Python version | Upload date | Hashes |
|---|---|---|---|---|
| Filename, size sfgad-0.1.2.tar.gz (27.4 kB) | File type Source | Python version None | Upload date | Hashes View hashes |
