Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fitted and train error... #33

Open
coforfe opened this issue Jul 27, 2021 · 2 comments
Open

Fitted and train error... #33

coforfe opened this issue Jul 27, 2021 · 2 comments

Comments

@coforfe
Copy link

coforfe commented Jul 27, 2021

Hi Matt,

Thanks for this package, as well as, the whole time series ecosystem you are building!.

Is it a way to get the fitted values when training a model (on training data) in a similar way as with forecast package ?.
And evaluate the error?. You can get test error, but sorry I could not find the way to get that for the train set.

I am looking for a way to asses if the model is overfitted.

Thanks!
Carlos.

@mdancho84
Copy link
Contributor

Hi @coforfe , thanks for the kind words. The ecosystem is really coming together.

For GluonTS models, we don't store the fitted values because they aren't stored in the GluonTS model objects.

I don't know if you can predict backwards. I have to see an implementation where the gluonts model predicts the training data. If this is possible, we can then include fitted data inside the modeltime objects.

@coforfe
Copy link
Author

coforfe commented Jul 27, 2021

Hi Matt,

Thanks for the clarifications!

Well, in the same direction you mention, it is possible to run several models with different lookback_length values. It is not optimum, but at least you have some sense of the level of error.

Thanks again!.
Carlos.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants