Improving the Accuracy of a Two-Stage Algorithm in Evolutionary Product Unit Neural Networks for Classification by Means of Feature Selection

@inproceedings{TallnBallesteros2011ImprovingTA,
  title={Improving the Accuracy of a Two-Stage Algorithm in Evolutionary Product Unit Neural Networks for Classification by Means of Feature Selection},
  author={Antonio J. Tall{\'o}n-Ballesteros and C{\'e}sar Herv{\'a}s-Mart{\'i}nez and Jos{\'e} Crist{\'o}bal Riquelme Santos and Roberto Ruiz S{\'a}nchez},
  booktitle={IWINAC},
  year={2011}
}
This paper introduces a methodology that improves the accuracy of a two-stage algorithm in evolutionary product unit neural networks for classification tasks by means of feature selection. A couple of filters have been taken into consideration to try out the proposal. The experimentation has been carried out on seven data sets from the UCI repository that report test mean accuracy error rates about twenty percent or above with reference classifiers such as C4.5 or 1-NN. The study includes an… CONTINUE READING

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