Using DropoutLayer in neural network (not only in CNN)
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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
Greg Heath
le 30 Août 2018
OVERFITTING IS NOT "THE" PROBLEM!
"THE" PROBLEM IS
"OVERTRAINING" an overfit net!!!
Hope this is clear!
Greg
Mario Schweda
le 29 Avr 2020
I´m looking for the same. A droput layer for simple networks like fitnet. Not only for CNNs.
Junwei Liu
le 26 Fév 2021
have you solve this problem?I have met the seem problem
Réponses (1)
Moses Wayne
le 16 Août 2017
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)
4 commentaires
Andy_daodao
le 16 Août 2017
Eman Marzban
le 29 Août 2018
Did you find a solution to this problem?
Thanks
Lingies Santhirasekaran
le 18 Juin 2019
Did anyone found a way to implement dropout in Matlab ?
Thanks
belen celik
le 25 Août 2019
how can dropoutLayer be implemented in new=newff() type of network?
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