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...

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Bibliographic Details
Main Authors: J. T. Zhu, C. Lin, H. B. Xiao, J. H. Fan, D. Bastieri, G. G. Wang
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:The Astrophysical Journal
Subjects:
Online Access:https://doi.org/10.3847/1538-4357/acca85