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Using gamma regression for photometric redshifts of survey galaxies

  • J. Elliott
  • , R. S. De Souza
  • , A. Krone-Martins
  • , E. Cameron
  • , E. E.O. Ishida
  • , J. Hilbe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Machine learning techniques offer a plethora of opportunities in tackling big data within the astronomical community. We present the set of Generalized Linear Models as a fast alternative for determining photometric redshifts of galaxies, a set of tools not commonly applied within astronomy, despite being widely used in other professions. With this technique, we achieve catastrophic outlier rates of the order of ~1%, that can be achieved in a matter of seconds on large datasets of size ~1;000;000. To make these techniques easily accessible to the astronomical community, we developed a set of libraries and tools that are publicly available.

Original languageEnglish
Title of host publicationThe Universe of Digital Sky Surveys - A Meeting to Honour the 70th Birthday of Massimo Capaccioli
EditorsGiuseppe Longo, Maurizio Paolillo, Nicola R. Napolitano, Marcella Marconi, Enrichetta Iodice
PublisherKluwer Academic Publishers
Pages91-96
Number of pages6
ISBN (Print)9783319193298
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventConference on Universe of Digital Sky Surveys, 2014 - Naples, Italy
Duration: 25 Nov 201428 Nov 2014

Publication series

NameAstrophysics and Space Science Proceedings
Volume42
ISSN (Print)1570-6591
ISSN (Electronic)1570-6605

Conference

ConferenceConference on Universe of Digital Sky Surveys, 2014
Country/TerritoryItaly
CityNaples
Period25/11/1428/11/14

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