Pruned Neural Networks for Regression

@inproceedings{Setiono2000PrunedNN,
  title={Pruned Neural Networks for Regression},
  author={Rudy Setiono and Wee Kheng Leow},
  booktitle={PRICAI},
  year={2000}
}
Neural networks have been widely used as a tool for regression. They are capable of approximating any function and they do not require any assumption about the distribution of the data. The most commonly used architectures for regression are the feedforward neural networks with one or more hidden layers. In this paper, we present a network pruning algorithm which determines the number of units in the input and hidden layers of the networks. We compare the performance of the pruned networks to… CONTINUE READING