I’m new to TMVA. I met a problem when trying MNIST multiclassification in pyTMVA.
My purpose is to mimic the well-known MNIST classification code in pyTMVA.
It has 60K events for training and 10K events for testing.
Thanks to the good compatibility, I could build the model easily. Now I got about 97.8% validation accuracy.
The only problem left is the validation set!
I want to train my network using all the 60K training events, without validation error check.
And test my network after all the training epochs end, using 10K testing events.
However, my TMVA automatically splits my training events into 48K training set and 12K validation set.
How can I deal with this problem?
Is there any option to set the validation fraction, so that I can give more the training event number?
There was, for TMlpANN, but not for DNN, according to the Users Guide…