• DOI:10.1109/TSMCB.2012.2227469
Corpus ID: 529726

Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach

@article{Xue2013ParticleSO,
  title={Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach},
  author={Bing Xue and M. Zhang and W. Browne},
  journal={IEEE Transactions on Cybernetics},
  year={2013},
  volume={43},
  pages={1656-1671}
}

Bing Xue, M. Zhang, W. Browne

Published 2013

Computer Science, Mathematics, Medicine

IEEE Transactions on Cybernetics

Classification problems often have a large number of features in the data sets, but not all of them are useful for classification. Irrelevant and redundant features may even reduce the performance. Feature selection aims to choose a small number of relevant features to achieve similar or even better classification performance than using all features. It has two main conflicting objectives of maximizing the classification performance and minimizing the number of features. However, most existing… CONTINUE READING

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