Galaxy classification: A machine learning analysis of GAMA catalogue data

no code implementations • 18 Mar 2019 • Aleke Nolte, Lingyu Wang, Maciej Bilicki, Benne Holwerda, Michael Biehl

We present a machine learning analysis of five labelled galaxy catalogues from the Galaxy And Mass Assembly (GAMA): The SersicCatVIKING and SersicCatUKIDSS catalogues containing morphological features, the GaussFitSimple catalogue containing spectroscopic features, the MagPhys catalogue including physical parameters for galaxies, and the Lambdar catalogue, which contains photometric measurements.

BIG-bench Machine Learning Classification +2