Combining support vector regression with feature selection for multivariate calibration

@article{Li2008CombiningSV,
  title={Combining support vector regression with feature selection for multivariate calibration},
  author={Guozheng Li and Hao-Hua Meng and Mary Yang and Jack Y. Yang},
  journal={Neural Computing and Applications},
  year={2008},
  volume={18},
  pages={813-820}
}
Multivariate calibration is a classic problem in the analytical chemistry field and frequently solved by partial least squares (PLS) and artificial neural networks (ANNs) in the previous works. The spaciality of multivariate calibration is high dimensionality with small sample. Here, we apply support vector regression (SVR) as well as ANNs, and PLS to the multivariate calibration problem in the determination of the three aromatic amino acids (phenylalanine, tyrosine and tryptophan) in their… CONTINUE READING
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