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+1 vote
in Machine Learning by (160 points)
To solve any problem when we can use genetic algorithms as opposed to neural networks & vice versa. I saw some examples where both are mixed. I need a good comparison between these two methods in some cases.

1 Answer

+2 votes
by (10.9k points)
edited by

@Joy_Lewis , Following are some basic difference between the two methods:

  • Genetic algorithms are mainly used in generating high-quality solutions to optimization and other search problems. Neural network is used to represent complex relationships between inputs and outputs. It has the ability to learn to classify item it has not seen before.
  • Genetic algorithms is a type of optimization algorithm while Neutral network is a type of mathematical model.
  • Genetic algorithm takes a long time to find an acceptable solution but Neutral network almost instantly classify new inputs, a Neutral network.
  • Genetic algorithms can generate new patterns in a structure, while Neutral networks classify existing networks based on their training data.
  • Lastly, Genetic algorithms works on discrete data and Neutral networks work on continuous data.

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