Bankruptcy prediction model using cost-sensitive extreme gradient boosting in the context of imbalanced datasets

Wirot Yotsawat, Kanyalag Phodong, Thawatchai Promrat, Pakaket Wattuya

Open source

DOI
10.11591/ijece.v13i4.pp4683-4691
Published
2023-08-01
Container
International Journal of Electrical and Computer Engineering (IJECE)
Publisher
Institute of Advanced Engineering and Science
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.11591/ijece.v13i4.pp4683-4691,
  title = {Bankruptcy prediction model using cost-sensitive extreme gradient boosting in the context of imbalanced datasets},
  author = {Wirot Yotsawat and Kanyalag Phodong and Thawatchai Promrat and Pakaket Wattuya},
  year = {2023},
  journal = {International Journal of Electrical and Computer Engineering (IJECE)},
  doi = {10.11591/ijece.v13i4.pp4683-4691},
  url = {https://doi.org/10.11591/ijece.v13i4.pp4683-4691}
}

RIS

TY  - JOUR
TI  - Bankruptcy prediction model using cost-sensitive extreme gradient boosting in the context of imbalanced datasets
AU  - Wirot Yotsawat
AU  - Kanyalag Phodong
AU  - Thawatchai Promrat
AU  - Pakaket Wattuya
PY  - 2023
JO  - International Journal of Electrical and Computer Engineering (IJECE)
DO  - 10.11591/ijece.v13i4.pp4683-4691
UR  - https://doi.org/10.11591/ijece.v13i4.pp4683-4691
ER  - 

APA

Yotsawat, W., Phodong, K., Promrat, T., & Wattuya, P. (2023). Bankruptcy prediction model using cost-sensitive extreme gradient boosting in the context of imbalanced datasets. International Journal of Electrical and Computer Engineering (IJECE). https://doi.org/10.11591/ijece.v13i4.pp4683-4691

Source records