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I tried to determine the application scenarios for RBM
And whether RBM has irreplaceable characteristics compared with neural network
In the test code DeepNetworkTrainingRBM
I commented out the RBM part, trying to compare the training effect of neural network without RBM
And then I was surprised
Cut off the connection between RBM and neural network
RBM still has an influence on the training results of neural network
Training error 0.26->0.06
Logically speaking
The hyper-parameter configuration of neural network is not good, which may lead to high training error
It should not be associated with irrelevant RBM
Because of this, I am not sure whether the neural network hyper-parameter need to be adjusted
win7 64
Shark-4.0.1
DeepNetworkTrainingRBM
I change the flag_rbm, test error(0.26, 0.06) will change a lot, And they don't have relation at all.
How could this happen?
DeepNetworkTrainingRBM.txt
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