Questions tagged [dropout]

Dropout is a technique to reduce overfitting during the training phase of a neural network.

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Why does adding a dropout layer improve deep/machine learning performance, given that dropout suppresses some neurons from the model?

If removing some neurons results in a better performing model, why not use a simpler neural network with fewer layers and fewer neurons in the first place? Why build a bigger, more complicated model ...
3
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1answer
211 views

Dropout in Deep Neural Networks

I was reading a paper published on Dropout. What I find difficulty in understanding that, In the training phase, a unit is present with a probability $p$ and not present with a probability $1-p$. In ...
3
votes
1answer
833 views

Probability of dropout growth

In the DNN literature, is there analysis or a term on a dropout ratio (oppositely-)proportional to the depth of a layer? By intuition, I'd like to dropout fewer neurons on the layers next to the ...
3
votes
1answer
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How does dropout work during testing in neural network?

The below paragraph is picked from the textbook Hands-On Machine Learning with sci-kit learn & Tensorflow. I couldn't understand what the author is trying to ...
1
vote
1answer
344 views

What is coadaptation of neurons in neural networks?

Looking for a bare minimum example (3 hidden units only maybe?) for what weights of a neural network with heavily coadapted weights would look like and showcase why they are bad. Also, how is ...