Exploring TeV Candidates of Fermi Blazars through Machine Learning
In this work, we make use of a supervised machine-learning algorithm based on Logistic Regression (LR) to select TeV blazar candidates from the 4FGL-DR2/4LAC-DR2, 3FHL, 3HSP, and 2BIGB catalogs. LR constructs a hyperplane based on a selection of optimal parameters, named features, and hyperparameter...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
IOP Publishing
2023-01-01
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Series: | The Astrophysical Journal |
Subjects: | |
Online Access: | https://doi.org/10.3847/1538-4357/acca85 |