Loss Function for a neural network
Hi everyone !
I did a neural network, but I want to do a loss function to demonstrate it works well and to explain with efficiency its performance.
Do you know how to set it up ?
Thanks a lot for your help 
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Hi @alois_borgognon,
- if you are using the native Deep Learning operator, you have to :
- choose a loss function in the parameters of this operator :
then you retrieve the results of the loss function in the model (mod output port) results :
- if you are using the deep learing extension (DL4J), you have to :
- choose the loss function in the parameters of the Tensor operator :
- connect the his output port of the Tensor operator to see the value of the loss function according to the epoch :
To obtain some help on this last deep learning extension, you can go to Sample -> Deep Learning in the repository :
Regards,
Lionel
- if you are using the native Deep Learning operator, you have to :
- choose a loss function in the parameters of this operator :
then you retrieve the results of the loss function in the model (mod output port) results :
- if you are using the deep learing extension (DL4J), you have to :
- choose the loss function in the parameters of the Tensor operator :
- connect the his output port of the Tensor operator to see the value of the loss function according to the epoch :
To obtain some help on this last deep learning extension, you can go to Sample -> Deep Learning in the repository :
Regards,
Lionel
- if you are using the native Deep Learning operator, you have to :
- choose a loss function in the parameters of this operator :
then you retrieve the results of the loss function in the model (mod output port) results :
- if you are using the deep learing extension (DL4J), you have to :
- choose the loss function in the parameters of the Tensor operator :
- connect the his output port of the Tensor operator to see the value of the loss function according to the epoch :
To obtain some help on this last deep learning extension, you can go to Sample -> Deep Learning in the repository :
Regards,
Lionel