The High Cadence Transit Survey (HiTS)

For the classification, we used a training set constructed using a combination of cross-matched catalogs, visual inspection, transfer/active learning, and data augmentation. The classification model consists of several random forest classifiers organized in a hierarchical scheme. The classifier accuracy estimated on a test set is approximately 97%.

In the unlabeled data, 3485 sources were classified as variables, of which 1321 were classified as periodic. Among the periodic classes, we discovered with high confidence one {delta} Scuti, 39 eclipsing binaries, 48 rotational variables, and 90 RR Lyrae, and for the nonperiodic classes, we discovered one cataclysmic variable, 630 QSOs, and one supernova candidate.