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I wonder if there is research, patents, or libraries using Genetic algorithms (GA) to improve Neural Networks. I don't find anything in the subject. For example:

  1. use GA to find better parameters in a NN. So the chromosome will be [learning rate, activation function, layers number, layers size, dropout factor] and the fit function minimize computational cost to reach NN 95% accuracy.
  2. use GA to mix your NN input data and generate new data to adjust.
  3. use GA to mix several small NN, different types, and find the perfect mix for better predictions.
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    $\begingroup$ Are you aware of neuro-evolution? $\endgroup$ – nbro Aug 9 at 10:53

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