I use a simple dnn_trainer to perform a classification (<100 features, 3 labels). This is necessary in my case because the size of the neural network on the different systems is created dynamically for each user. At the same time, I limit the maximum duration of training via the step-by-step training (train_one_step).
This works fine but now I want to improve the normalization and save the normalization vector to the DNN.
Is there a way (similar to http://dlib.net/krr_classification_ex.cpp.html) to create a normalizer for a dnn trainier?
Best regards,
Fohlen
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Hello @Davis,
I use a simple
dnn_trainer
to perform a classification (<100 features, 3 labels). This is necessary in my case because the size of the neural network on the different systems is created dynamically for each user. At the same time, I limit the maximum duration of training via the step-by-step training (train_one_step).This works fine but now I want to improve the normalization and save the normalization vector to the DNN.
Is there a way (similar to http://dlib.net/krr_classification_ex.cpp.html) to create a normalizer for a dnn trainier?
Best regards,
Fohlen
Sorry, I've found out that the normalizer can be easily serialized and deserialized.