Extreme learning machines for credit scoring: An empirical evaluation

@article{Bequ2017ExtremeLM,
  title={Extreme learning machines for credit scoring: An empirical evaluation},
  author={Artem Bequ{\'e} and Stefan Lessmann},
  journal={Expert Syst. Appl.},
  year={2017},
  volume={86},
  pages={42-53}
}
Abstract Classification algorithms are used in many domains to extract information from data, predict the entry probability of events of interest, and, eventually, support decision making. This paper explores the potential of extreme learning machines (ELM), a recently proposed type of artificial neural network, for consumer credit risk management. ELM possess some interesting properties, which might enable them to improve the quality of model-based decision support. To test this, we… CONTINUE READING
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