Investigation and improvement of multi-layer perceptron neural networks for credit scoring

作者：

Highlights：

• We present an Average Random Choosing method which increases 0.04 classification accuracy.

• Investigate different MLP models and get the best model with accuracy of 87%.

• Accuracy increases when the model has more hidden neurons.

摘要

•We present an Average Random Choosing method which increases 0.04 classification accuracy.•Investigate different MLP models and get the best model with accuracy of 87%.•Accuracy increases when the model has more hidden neurons.

论文关键词：Credit scoring,Neural networks,Back propagation

论文评审过程：Available online 10 December 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.12.006