The role of the Dropout layer in the Convolutional Neural Network (CNN) is - Code World

The role of the Dropout layer in the Convolutional Neural Network (CNN) is

Others 2020-10-15 17:43:26 views: null

Dropout refers to randomly letting the weights of some hidden layer nodes of the network not work during model training. Those nodes that do not work can be temporarily considered as not part of the network structure, but their weights must be retained (just temporarily not updated). Because it might have to work again the next time the sample is entered. When training a neural network model, if the training sample is small, in order to prevent the model from overfitting, Dropout can be used as a trikc for selection.

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