A novel embedded min-max approach for feature selection in nonlinear Support Vector Machine classification

Asunción Jiménez-Cordero, Juan-Miguel Morales, Salvador Pineda. A novel embedded min-max approach for feature selection in nonlinear Support Vector Machine classification. European Journal of Operational Research, 293(1):24-35, 2021. [doi]

@article{Jimenez-Cordero21-0,
  title = {A novel embedded min-max approach for feature selection in nonlinear Support Vector Machine classification},
  author = {Asunción Jiménez-Cordero and Juan-Miguel Morales and Salvador Pineda},
  year = {2021},
  doi = {10.1016/j.ejor.2020.12.009},
  url = {https://doi.org/10.1016/j.ejor.2020.12.009},
  researchr = {https://researchr.org/publication/Jimenez-Cordero21-0},
  cites = {0},
  citedby = {0},
  journal = {European Journal of Operational Research},
  volume = {293},
  number = {1},
  pages = {24-35},
}