Multiple extreme learning machines for a two-class imbalance corporate life cycle prediction

@article{Lin2013MultipleEL,
  title={Multiple extreme learning machines for a two-class imbalance corporate life cycle prediction},
  author={Sin-Jin Lin and Chingho Chang and Ming-Fu Hsu},
  journal={Knowl.-Based Syst.},
  year={2013},
  volume={39},
  pages={214-223}
}
Pre-warning of whether a corporate will fall into a decline stage in the near future is an emerging issue in financial management. Improper decision-making by firms incurs a higher possibility to cause financial crisis (distress) and deteriorates the soundness of financial markets. The aim of this study is to establish a novel prediction mechanism based on combining the sampling technique (synthetic minority oversampling technique; SMOTE), feature selection ensemble (original, intersection, and… CONTINUE READING

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