rolandzitny / nsga2-neuroevolution

NSGA2 to design and optimize LSTM Autoencoder

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Automatic design and optimization of neural network using evolutionary algorithm NSGA2

Using a multi-objective algorithm to design and optimize the structure of a neural network for processing a selected benchmark dataset. A set of networks will be designed that are Pareto optimal in terms of accuracy, computational complexity, and memory usage.

  • Python, Tensorflow
  • NSGA2

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NSGA2 to design and optimize LSTM Autoencoder

License:MIT License


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Language:Python 100.0%