@article{029c2a2a001040abab4ce44e25e54daa,
title = "A probabilistic approach to emission-line galaxy classification",
keywords = "methods: data analysis, galaxies: evolution, galaxies: general, galaxies: nuclei, galaxies: star formation, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics, Statistics - Machine Learning",
author = "\{de Souza\}, R.\textasciitilde{}S. and M.\textasciitilde{}L.\textasciitilde{}L. Dantas and M.\textasciitilde{}V. Costa-Duarte and E.\textasciitilde{}D. Feigelson and M. Killedar and Lablanche, \{P. -Y.\} and R. Vilalta and A. Krone-Martins and R. Beck and F. Gieseke",
year = "2017",
month = dec,
day = "1",
doi = "10.1093/mnras/stx2156",
language = "English",
volume = "472",
pages = "2808--2822",
journal = "Monthly Notices of the Royal Astronomical Society (MNRAS)",
issn = "0035-8711",
publisher = "Oxford University Press (OUP)",
number = "3",
}