Automated Classification of Periodic Variable Stars Using Machine Learning
UPSILoN (AUtomated Classification of Periodic Variable Stars using MachIne LearNing) aims to classify periodic variable stars such as Delta Scuti stars, RR Lyraes, Cepheids, Type II Cepheids, eclipsing binaries, and long-period variables (i.e. superclasses), and their subclasses (e.g. RR Lyrae ab, c, d, and e types) using well-sampled light curves from any astronomical time-series surveys in optical bands regardless of their survey-specific characteristics such as color, magnitude, sampling rate, etc (Kim & Bailer-Jones 2015, A&A accepted, http://arxiv.org/abs/1512.01611).
Visit https://github.com/dwkim78/upsilon for details.