Estimating stellar atmospheric parameters based on LASSO and support-vector regression

@article{Lu2015EstimatingSA,
  title={Estimating stellar atmospheric parameters based on LASSO and support-vector regression},
  author={Yu Lu and Xiangru Li},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2015},
  volume={452},
  pages={1394-1401}
}
  • Yu Lu, Xiangru Li
  • Published 3 August 2015
  • Computer Science
  • Monthly Notices of the Royal Astronomical Society
A scheme for estimating atmospheric parameters T$_{eff}$, log$~g$, and [Fe/H] is proposed on the basis of Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Haar wavelet. The proposed scheme consists of three processes. A spectrum is decomposed using the Haar wavelet transform and low-frequency components at the fourth level are considered as candidate features. Then, spectral features from the candidate features are detected using the LASSO algorithm to estimate the… 

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