Parameter Optimization of Extreme Learning Machine Using Bacterial Foraging Algorithm

@inproceedings{Cho2007ParameterOO,
  title={Parameter Optimization of Extreme Learning Machine Using Bacterial Foraging Algorithm},
  author={J. Cho and Myung-Geun Chun and Dae-Jong Lee},
  year={2007}
}
Recently, Extreme learning machine(ELM), a novel learning algorithm having much faster than the traditional gradient-based learning algorithm, was proposed for single-hidden-layer feedforward neural networks (SLFNs). Usually, the initial input weights and hidden biases of ELM are randomly chosen, and then the output weights are analytically determined by using Moore-Penrose (MP) generalized inverse. However, ELM may need higher number of hidden neurons due to the random determination of the… CONTINUE READING

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