Closed noparkee closed 6 months ago
Hello, I think there is a bit of confusion here.
This is a good thread to a similar question explaining what in/out accuracy means https://github.com/facebookresearch/DomainBed/issues/53#issuecomment-849509189
If I understood correctly, env_x_out
is a smaller split used to identify hyperparameters and env_x_in
is for training and final evaluation. Hope this helps.
Yes, @abalhomaid is correct. This is a design decision, and including the full dataset could make checkpoint selection difficult for some algorithms (you need some validation data for this). Closing. Feel free to re-open if there is still confusion.
Hello. I have a question about in/out accuracy when measuing performance.
If there are n domains for a dataset, we divide each domain into a train set (in) and a test set (out). Then, train the model using the train data of the domains except the target domain. After model selection, when measuring performance, why do we evaluate with the test_in_acc_key of the target domain, i.e., the train set? Why not the whole dataset and why not the test set?
Thank you!