Binary grey wolf optimization approaches for feature selection

@article{Emary2016BinaryGW,
  title={Binary grey wolf optimization approaches for feature selection},
  author={Eid Emary and Hossam M. Zawbaa and Aboul Ella Hassanien},
  journal={Neurocomputing},
  year={2016},
  volume={172},
  pages={371-381}
}
In this work, a novel binary version of the grey wolf optimization (GWO) is proposed and used to select optimal feature subset for classification purposes. Grey wolf optimizer (GWO) is one of the latest bioinspired optimization techniques, which simulate the hunting process of grey wolves in nature. The binary version introduced here is performed using two different approaches. In the first approach, individual steps toward the first three best solutions are binarized and then stochastic… CONTINUE READING
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