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NeuralNetwork Operator
Parameters
dropout
A single model can be used to simulate having a large number of different network architectures by randomly dropping out nodes during training. This is called dropout and offers a very computationally cheap and remarkably effective regularization method to reduce overfitting and generalization error in deep neural networks of all kinds.