DRAGNs in the Forest: Identifying Artifacts with Random Forest Models in the VLASS DRAGNs Catalog
Analysis
This article describes the application of Random Forest models to identify artifacts within the VLASS DRAGNs catalog. The use of machine learning techniques for astronomical data analysis is a growing trend, and this research likely contributes to improved data quality and analysis in radio astronomy. The specific details of the model and its performance would be crucial for a thorough evaluation.
Key Takeaways
- •Applies Random Forest models to identify artifacts in the VLASS DRAGNs catalog.
- •Contributes to improved data quality and analysis in radio astronomy.
- •Represents a use of machine learning in astronomical data processing.
Reference
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