Gaiaeclipsing binary and multiple systems. Supervised classification and self-organizing maps
M. Süveges, F. Barblan, I. Lecoeur-Taïbi, A. Prša, B. Holl, L. Eyer, A. Kochoska, N. Mowlavï, L. Rimoldini · Astronomy and Astrophysics · 2017
Context. Large surveys producing tera- and petabyte-scale databases require machine-learning and knowledge discovery methods to deal with the overwhelming quantity of data and the difficulties of extracting concise, meaningful information with reliable assessment of its uncertainty. This study investigates the potential of a few machine-learning methods for the automated analysis of eclipsing binaries in the data of such surveys.