rprop mlp node

[Tseraga]

Hi

i manage to get some good accuracy result for regression neural network using the RPROP mlp node .

however when i try to transfer the configuration to DL4J (as i needed more configuration details) , the accuracy seem to fall off drastically and i am at lost what parameter am i overlooking

thanks

[dora_gcs]

Hello @Tseraga ,

welcome in the Forum.

It is quiet challenging to give you a correct answer at his point. Could you please give us more detail about your model, your configurations etc. It would be better if you could share with us your workflow / dataset (without any sensitive data).

Please check this post it seems pretty similar to your problem perhaps it will be useful for you:

DL4J Neural Network vs. RPROP algorithms

Hello everyone! I have a problem with the efficiency of the DL4J algorithm for neural networks. More specifically, I want to train a neural network so that it correctly predicts the values from some dataset (so I have a regression problem). I have used as parameters the following values:  -Optimization algorithm: Stochastic Gradient Descent -Updater: Nesterovs -0.0001 as L2 regularization -learning rate: 0.01 -23 epochs on a dataset containing 307 input samples -loss function: Sum of erro…

Kind regards!

[Tseraga]

Hi
sorry for the late reply , got flooded with work recently

the input is 40 numerical variable to predict a final numerical variable

the configuration for the
rprop is
2 layer and 40 neuron
train : test : validate - 7:2:1
data set ~ 130 data point
iteration 300

for the dl4j configuraiton i tried
iteration 1
epoch : 100
batch : 100
updater SGD
optimizer SGD

the generic rprop mlp was actually situable for my problem but i got asked in detail why the configuration was chosen (Activation function) , which i cant answer , which is why i testing with dl4j

Thanks

P.S : will upload the workflow when i am free