SA: Automated classification of eclipsing binary systems in the VVV Survey – Daza Perilla

In this study, we use a recently published catalogue of one hundred EBSs, classified by fine-tuning theoretical models according to contact, detached or semi-detached classes. We describe the method implemented to obtain supervised machine learning models, capable of classifying EBSs using information extracted from the light curves of variable object candidates in the phase space.