Density-Preserving Sampling: Robust and Efficient Alternative to Cross-Validation for Error Estimation

Marcin Budka, Bogdan Gabrys. Density-Preserving Sampling: Robust and Efficient Alternative to Cross-Validation for Error Estimation. IEEE Transactions on Neural Networks, 24(1):22-34, 2013. [doi]

@article{BudkaG13,
  title = {Density-Preserving Sampling: Robust and Efficient Alternative to Cross-Validation for Error Estimation},
  author = {Marcin Budka and Bogdan Gabrys},
  year = {2013},
  doi = {10.1109/TNNLS.2012.2222925},
  url = {http://dx.doi.org/10.1109/TNNLS.2012.2222925},
  researchr = {https://researchr.org/publication/BudkaG13},
  cites = {0},
  citedby = {0},
  journal = {IEEE Transactions on Neural Networks},
  volume = {24},
  number = {1},
  pages = {22-34},
}