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[ascl:2403.002] DistClassiPy: Distance-based light curve classification

DistClassiPy uses different distance metrics to classify objects such as light curves. It provides state-of-the-art performance for time-domain astronomy, and offers lower computational requirements and improved interpretability over traditional methods such as Random Forests, making it suitable for large datasets. DistClassiPy allows fine-tuning based on scientific objectives by selecting appropriate distance metrics and features, which enhances its performance and improves classification interpretability.

Code site:
https://github.com/sidchaini/DistClassiPy/
Described in:
https://ui.adsabs.harvard.edu/abs/2024arXiv240312120C
Bibcode:
2024ascl.soft03002C

Views: 456

ascl:2403.002
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