In this paper, the authors describe the use of data mining techniques to search for radio-emitting galaxies with a bent-double morphology. In the past, astronomers from the FIRST (Faint Images of the Radio Sky at Twenty-cm) survey identified these galaxies through visual inspection. This was not only subjective but also tedious as the on-going survey now covers 8000 square degrees, with each square degree containing about 90 galaxies. In this paper, they describe how data mining can be used to automate the identification of these galaxies. They discuss the challenges faced in defining meaningful features that represent the shape of …
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Lawrence Livermore National Lab., CA (United States)
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In this paper, the authors describe the use of data mining techniques to search for radio-emitting galaxies with a bent-double morphology. In the past, astronomers from the FIRST (Faint Images of the Radio Sky at Twenty-cm) survey identified these galaxies through visual inspection. This was not only subjective but also tedious as the on-going survey now covers 8000 square degrees, with each square degree containing about 90 galaxies. In this paper, they describe how data mining can be used to automate the identification of these galaxies. They discuss the challenges faced in defining meaningful features that represent the shape of a galaxy and their experiences with ensembles of decision trees for the classification of bent-double galaxies.
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Kamath, C.; Cantu-Paz, E.; Fodor,I & Tang,N A.Using Data Mining to Find Bent-Double Radio Galaxies in the FIRST Survey,
article,
June 22, 2001;
California.
(https://digital.library.unt.edu/ark:/67531/metadc1412747/:
accessed May 16, 2024),
University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu;
crediting UNT Libraries Government Documents Department.
