Using DropoutLayer in neural network (not only in CNN)

hey guys,
i am using matlab to create a Neural Network for a Regression Problem.
to avoid overfitting i want to add a dropoutLayer after the Input layer, but i see only examples for CNN.
did someone knows, how to add a dropoutLayer in noraml neural Network or Setting the Options of neural Network(not CNN)
thanks

3 commentaires

OVERFITTING IS NOT "THE" PROBLEM!
"THE" PROBLEM IS
"OVERTRAINING" an overfit net!!!
Hope this is clear!
Greg
I´m looking for the same. A droput layer for simple networks like fitnet. Not only for CNNs.
have you solve this problem?I have met the seem problem

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Réponses (1)

The "dropoutLayer" class seems to be able to solve your problem. Calling it with no arguments returns a layer with 0.5 probability of dropping an input element. This layer can then be used in the training of your neural network. Here is a code example of creating a dropout layer with .6 probability of dropping an input element:
myLayer = dropoutLayer(0.6)
I have linked the documentation to the "dropoutLayer" class here.

4 commentaires

hey, thanks for your answer.
i know the dropoutLayer calss
i create a network using net = network. how can i add this dropoutLayer into net. i have tried e.g. net.layers{1} = drpoutLayer(0.5), but it works not.
thanks
Did you find a solution to this problem?
Thanks
Did anyone found a way to implement dropout in Matlab ?
Thanks
how can dropoutLayer be implemented in new=newff() type of network?

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Question posée :

le 16 Août 2017

Commenté :

le 26 Fév 2021

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