Stacking for machine learning redshifts applied to SDSS galaxies

no code implementations • 19 Feb 2016 • Roman Zitlau, Ben Hoyle, Kerstin Paech, Jochen Weller, Markus Michael Rau, Stella Seitz

We observe a significant improvement of between 1. 9% and 21% on all computed metrics when stacking is applied to weak learners (such as SOMs and decision trees).

BIG-bench Machine Learning

Anomaly detection for machine learning redshifts applied to SDSS galaxies

no code implementations • 27 Mar 2015 • Ben Hoyle, Markus Michael Rau, Kerstin Paech, Christopher Bonnett, Stella Seitz, Jochen Weller

We present an analysis of anomaly detection for machine learning redshift estimation.

Cosmology and Nongalactic Astrophysics