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

refactor: use train data if test data is empty for a cluster #466

Merged
merged 1 commit into from
Jan 18, 2024

Conversation

sathvikbhagavan
Copy link
Member

As we sample train data and test data, it can happen that test data in one of the clusters is empty that leads to spurious CI failures.

This approach uses train data for obtaining best model in a cluster if there is no test data available as a fallback instead of erroring.

Copy link

codecov bot commented Jan 13, 2024

Codecov Report

Attention: 1 lines in your changes are missing coverage. Please review.

Comparison is base (4f069df) 65.41% compared to head (12a0529) 78.31%.

Files Patch % Lines
lib/SurrogatesMOE/src/SurrogatesMOE.jl 92.30% 1 Missing ⚠️
Additional details and impacted files
@@             Coverage Diff             @@
##           master     #466       +/-   ##
===========================================
+ Coverage   65.41%   78.31%   +12.89%     
===========================================
  Files          23       23               
  Lines        3146     3159       +13     
===========================================
+ Hits         2058     2474      +416     
+ Misses       1088      685      -403     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

@ChrisRackauckas ChrisRackauckas merged commit 45eb062 into SciML:master Jan 18, 2024
8 checks passed
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

Successfully merging this pull request may close these issues.

2 participants