Test_model.Elbo, is it the right.

[ValeriiBaidin]

I wonder about Model.Elbo. Should it be the same, after predict(test_corp, train_model), if test_corp are equal train_corp. So I've just predicted model on the same corpus. Alpha, Beta, Elogtheta are the same. I've tested it and I could get the same elbo. I also use update_elbo(model) function at the end of predict() function.

Would you check my understanding? Why I can't get the same elbo?

I really appreciate any help you can provide.

[ericproffitt]

Hi Valerii,

So only the essential variables of the input model are transferred over to the output model. Nonessential variables (such as the ELBO) are not transferred. In fact it doesn't, in general, make sense to transfer the ELBO, since most of the time the train and test corpora will be different.

The output model can be trained if you'd like, however its primary purpose is to be a container for topic information. Do you have a particular use case in mind where you need to transfer all the model data from the input model to the output model?

[ValeriiBaidin]

Hi. Thank you for your answer.

I need some measure of model quality that I can use on testing data. So I think I can use Elbo for this purpose.

I've added to the end of function predict at modulutils.jl, update_elbo!(model). Can I do it?

What do you think about it? Thank you in advance.

[ericproffitt]

Sure, that should be fine.

Actually on second thought, this won't work as is.

You will also need to set all the _old global variables equal to their regular counterparts, e.g. for LDA you would need to set

model.beta_old = copy(train_model.beta)

[ValeriiBaidin]

thank you, it's work, If it is possible, would you add these two lines in the master?

Thank you so much.!!

[ericproffitt]

I may consider it, however updating the ELBO can be time consuming for large models, so for now I'm going to leave it to the user to do manually if they so desire.