180 citations · 285 across the 3 of their papers we have counts for
Showing 2014 · astro-ph.IMShow all
2 papers · 2 filters
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…