Questions tagged [dropout]

For questions related to the concept of dropout, which refers to the dropping out units in a neural network (NN), during the training of the NN, so that to avoid overfitting. The dropout method is a regularisation technique, which was introduced in "Dropout: A Simple Way to Prevent Neural Networks from Overfitting" (2014) by Nitish Srivastava et al.

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Should I remove the units of a neural network or increase dropout?

When adding dropout to a neural network, we are randomly removing a fraction of the connections (setting those weights to zero for that specific weight update iteration). If the dropout probability is ...
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3answers
1k views

What to do if CNN cannot overfit a training set on adding dropout?

I have been trying to use CNN for a regression problem. I followed the standard recommendation of disabling dropout and overfitting a small training set prior to trying for generalization. With a 10 ...
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2answers
2k views

Is pooling a kind of dropout?

If I got well the idea of dropout, it allows improving the sparsity of the information that comes from one layer to another by setting some weights to zero. On the other hand, pooling, let's say max-...
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1answer
385 views

Why is my validation/test accuracy higher than my training accuracy

Is this due to my dropout layers being disabled during evaluation? I'm classifying the CIFAR-10 dataset with a CNN using the Keras library. There are 50000 samples in the training set; I'm using a ...