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Tagged with regularization deep-learning
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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 ...
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