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20142023
most citedPhotometric redshift analysis in the Dark Energy Survey Science Verification data

180 citations · 351 across the 7 of their papers we have counts for

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Showing 2014Show all

2 papers · 1 filter

astro-ph.IM2014★ 63 cited

Feature importance for machine learning redshifts applied to SDSS galaxies

Ben Hoyle, Markus Michael Rau, Roman Zitlau +2

We present an analysis of importance feature selection applied to photometric redshift estimation using the machine learning architecture Decision Trees with the ensemble learning…

astro-ph.IM2014★ 180 cited

Photometric redshift analysis in the Dark Energy Survey Science Verification data

C. Sánchez, M. Carrasco Kind, H. Lin +74

We present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification (SV) period of observation…