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Multidimensional data driven classification of emission-line galaxies

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Title: Multidimensional data driven classification of emission-line galaxies
Authors: Stampoulis, V
Van Dyk, D
Kashyap, VL
Zezas, A
Item Type: Journal Article
Abstract: We propose a new soft clustering scheme for classifying galaxies in different activity classes using simultaneously four emission-line ratios: log ([NII]/H α), log ([SII]/H α), log ([OI]/H α), and log ([OIII]/H β). We fit 20 multivariate Gaussian distributions to the four-dimensional distribution of these lines obtained from the Sloan Digital Sky Survey in order to capture local structures and subsequently group the multivariate Gaussian distributions to represent the complex multidimensional structure of the joint distribution of galaxy spectra in the four-dimensional line ratio space. The main advantages of this method are the use of all four optical-line ratios simultaneously and the adoption of a clustering scheme. This maximizes the use of the available information, avoids contradicting classifications, and treats each class as a distribution resulting in soft classification boundaries and providing the probability for an object to belong to each class. We also introduce linear multidimensional decision surfaces using support vector machines based on the classification of our soft clustering scheme. This linear multidimensional hard clustering technique shows high classification accuracy with respect to our soft clustering scheme.
Issue Date: 1-May-2019
Date of Acceptance: 29-Jan-2019
URI: http://hdl.handle.net/10044/1/67307
DOI: https://dx.doi.org/10.1093/mnras/stz330
ISSN: 0035-8711
Publisher: Oxford University Press (OUP)
Start Page: 1085
End Page: 1102
Journal / Book Title: Monthly Notices of the Royal Astronomical Society
Volume: 485
Issue: 1
Copyright Statement: © 2019 The Author(s)Published by Oxford University Press on behalf of the Royal Astronomical Society. This is a pre-copy-editing, author-produced version of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The definitive publisher-authenticated version is available online at: [insert hyperlinked DOI]
Sponsor/Funder: National Science Foundation (US)
European Commission
Funder's Grant Number: DMS 15-13484
H2020-MSCA-RISE-2015-691164
Keywords: 0201 Astronomical And Space Sciences
Astronomy & Astrophysics
Publication Status: Published
Online Publication Date: 2019-02-11
Appears in Collections:Mathematics
Statistics
Faculty of Natural Sciences



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