Feature selection and classification in multiple class datasets: An application to KDD Cup 99 dataset

@article{BolnCanedo2011FeatureSA,
  title={Feature selection and classification in multiple class datasets: An application to KDD Cup 99 dataset},
  author={Ver{\'o}nica Bol{\'o}n-Canedo and Noelia S{\'a}nchez-Maro{\~n}o and Amparo Alonso-Betanzos},
  journal={Expert Syst. Appl.},
  year={2011},
  volume={38},
  pages={5947-5957}
}
In this work, a new method consisting of a combination of discretizers, filters and classifiers is presented. Its aim is to improve the performance results of classifiers but using a significantly reduced set of features. The method has been applied to a binary and to a multiple class classification problem. Specifically, the KDD Cup 99 benchmark was used for testing its effectiveness. A comparative study with other methods and the KDD winner was accomplished. The results obtained showed the… CONTINUE READING
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