Extraction of rules from artificial neural networks for nonlinear regression

@article{Setiono2002ExtractionOR,
  title={Extraction of rules from artificial neural networks for nonlinear regression},
  author={Rudy Setiono and Wee Kheng Leow and Jacek M. Zurada},
  journal={IEEE transactions on neural networks},
  year={2002},
  volume={13 3},
  pages={564-77}
}
Neural networks (NNs) have been successfully applied to solve a variety of application problems including classification and function approximation. They are especially useful as function approximators because they do not require prior knowledge of the input data distribution and they have been shown to be universal approximators. In many applications, it is desirable to extract knowledge that can explain how Me problems are solved by the networks. Most existing approaches have focused on… CONTINUE READING
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