DistClassiPy: Distance-based light curve classification
Abstract
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.
- Publication:
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Astrophysics Source Code Library
- Pub Date:
- March 2024
- Bibcode:
- 2024ascl.soft03002C
- Keywords:
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- Software