63 citations · 90 across the 2 of their papers we have counts for
2 papers
astro-ph.IM2016★ 27 cited
Stacking for machine learning redshifts applied to SDSS galaxies
Roman Zitlau, Ben Hoyle, Kerstin Paech +3
We present an analysis of a general machine learning technique called 'stacking' for the estimation of photometric redshifts. Stacking techniques can feed the photometric redshift…
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…