VizieR Online Data Catalog: Gaia Photometric Science Alerts (Hodgkin+, 2021)

JResults of binary classification for Gaia Science Alerts to distinguish between two classes of Galactic transient: young stellar objects (YSOs), and cataclysmic variables (CVs). The classifier employs a support vector machine (SVM), using the standard radial basis function (RBF) kernel in the scikit-learn package in Python. Probabilistic output was obtained through 5-fold cross-validation. We used a set of classified YSOs and CVs as a training set and predicted classifications for 1815 unknown alerts that have a counterpart in DR2. For a classification probability, P>0.95, we have classified 638 sources as new CVs, and 202 sources as new YSOs. We caution that this is a very simplistic classifier which uses only the magnitude, colour and parallax of the transients. This classifier also only considers two types of objects, so the list may be contaminated with a small number of other objects such as flare stars, variable stars or QSOs.

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