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.

Sign up for GitHub

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

Jump to bottom

Change the logic for model expiry to optional based on model freshness #86

Open
sayanchk opened this issue Mar 10, 2021 · 2 comments
Open

Change the logic for model expiry to optional based on model freshness #86

sayanchk opened this issue Mar 10, 2021 · 2 comments
Labels
feature Any new feature request reported help wanted Extra attention is needed

Comments

@sayanchk
Copy link
Collaborator

The current logic expires the model after k time units depending on the data frequency. This prevents forecasting for long terms. The expiry logic should be change to optional.
@sayanchk sayanchk self-assigned this Mar 10, 2021
@sayanchk sayanchk removed their assignment Oct 23, 2022
@sayanchk sayanchk added feature Any new feature request reported help wanted Extra attention is needed labels Oct 23, 2022
@mansi104-ai
Copy link

Hello , @sayanchk , I am an MLOps developer from India , can I help you with this issue?

@sayanchk
Copy link
Collaborator Author

@mansi104-ai Thanks for jumping into this. This setting makes the scorinf process too restrictive. Please go ahead and raise the PR with your changes.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
feature Any new feature request reported help wanted Extra attention is needed
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
2 participants
@sayanchk @mansi104-ai