Classifying Kepler light curves for 12,000 A and F stars using supervised feature-based machine learning

@article{Barbara2022ClassifyingKL,
  title={Classifying Kepler light curves for 12,000 A and F stars using supervised feature-based machine learning},
  author={Nicholas H. Barbara and Timothy R. Bedding and Ben D. Fulcher and Simon J. Murphy and Timothy Van Reeth},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2022}
}
With the availability of large-scale surveys like Kepler and TESS, there is a pressing need for automated methods to classify light curves according to known classes of variable stars. We introduce a new algorithm for classifying light curves that compares 7000 time-series features to find those which most effectively classify a given set of light curves. We apply our method to Kepler light curves for stars with effective temperatures in the range 6500–10,000 K. We show that the sample can be… 

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