$An investigation on the factors affecting machine learning classifications in $\gamma$-ray astronomy$

An investigation on the factors affecting machine learning classifications in $\gamma$-ray astronomy

We have investigated a number of factors that can have significant impacts on the classification performance of $\gamma$-ray sources detected by Fermi Large Area Telescope (LAT) with machine learning techniques. We show that a framework of automatic feature selection can construct a simple model w...

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Veröffentlicht in:	arXiv.org 2020-01
Hauptverfasser:	Luo, Shengda, Leung, Alex P, Hui, C Y, Li, K L
Format:	Artikel
Sprache:	eng
Schlagworte:	Active galactic nuclei Astronomy Classification Classifiers Confidence Gamma rays Machine learning Millisecond pulsars Statistical methods Test sets Training Variation
Online-Zugang:	Volltext
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An investigation on the factors affecting machine learning classifications in \(\gamma\)-ray astronomy