Deriving the Stellar Labels of LAMOST Spectra with the Stellar LAbel Machine (SLAM)

  title={Deriving the Stellar Labels of LAMOST Spectra with the Stellar LAbel Machine (SLAM)},
  author={Bo Zhang and Chao Liu and Licai Deng},
  journal={arXiv: Solar and Stellar Astrophysics},
  • Bo Zhang, C. Liu, L. Deng
  • Published 23 August 2019
  • Physics
  • arXiv: Solar and Stellar Astrophysics
The LAMOST survey has provided 9 million spectra in its Data Release 5 (DR5) at R$\sim$1800. Extracting precise stellar labels is crucial for such a large sample. In this paper, we report the implementation of the Stellar LAbel Machine (SLAM), which is a data-driven method based on Support Vector Regression (SVR), a robust non-linear regression technique. Thanks to the capability to model highly non-linear problems with SVR, SLAM generally can derive stellar labels over a wide range of spectral… Expand
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