can I see testing accuracy and loss graph in Neural network, like training graph?

4 vues (au cours des 30 derniers jours)
In classify() function can i set parameters to plot graph for testing accuracy and loss?
also what if I have not provided any validation data ie i have done two partions only training and test. Is there any problem?

Réponse acceptée

Raunak Gupta
Raunak Gupta le 12 Août 2020
Hi Krishna,
I assume by graph of the testing accuracy and loss; you mean epoch wise plot of the parameters for testing data. I think if you want to get the values for the testing data it is required to pass the data while training itself so that prediction can be made at every epoch and accordingly mini-batch accuracy and loss can be updated.
So essentially you need to pass testing data as validation data for calculating the accuracy and loss epoch wise.
For second question, it is completely fine to skip the validation data.
Hope this clarifies.
  7 commentaires
Raunak Gupta
Raunak Gupta le 11 Sep 2020
What is the typical difference you are seeing between different runs? If the difference is small, it may be due to the shuffling of the training data that happens between every epoch or at the very start of the training.
You may set the 'Shuffle' Name-value pair in trainingOptions to 'never' if this is the issue.
krishna Chauhan
krishna Chauhan le 13 Sep 2020
oh! I just did that
and it drop down the classification accuacy almost 20%
and about ur first part of question yes it differes by 1-2 %
thats I think high
Can u suggest anything ?
and what i can understand shuffling the data in every epoch is good. no?

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