Detecting wide binaries using machine learning algorithms (data repository)
Description
This dataset contains the pretrained model parameters and the data used for training the ML models developed for the tool available at WBS-Anomaly. The accompaning paper is titled "Predicting wide binaries and deviations from standard gravity using machine learning algorithms" Amoy Ashesh, Harsimran Kaur, Sandeep Aashish, 2025 (finalizing the manuscipt for publication). The work has been currently limited to the problem of identifying WBS only. The anomaly detection problem is an ongoing research work.
The folder for anomaly detection contains the repository made available by Chae, Kyu-Hyun and El-Badry, Kareem:
Chae, K.-H. (2024). Python scripts to test gravity with the dynamics of wide binary stars. Zenodo. https://doi.org/10.5281/zenodo.10652994
El-Badry, K. (2021). Wide binaries from Gaia eDR3 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4435257
Files
README.md
Additional details
Software
- Repository URL
- https://github.com/DespCAP/WBS-Anomaly
- Programming language
- Python, Jupyter Notebook
- Development Status
- Active
References
- Chae, K.-H. (2024). Python scripts to test gravity with the dynamics of wide binary stars. Zenodo. https://doi.org/10.5281/zenodo.10652994
- El-Badry, K. (2021). Wide binaries from Gaia eDR3 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4435257