Identifying Catastrophic Outlier Photometric Redshift Estimates in the COSMOS Field with Machine Learning Methods
We present the result of two binary classifier ensembled neural networks to identify catastrophic outliers for photo- z estimates within the COSMOS field utilizing only eight and five photometric bandpasses, respectively. Our neural networks can correctly classify 55.6% and 33.3% of the true positiv...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | The Astrophysical Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.3847/1538-4357/adbe62 |
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