Thanks to visit codestin.com
Credit goes to github.com

Skip to content

Comments

ENH: implement fusion with the global model in prediction#54

Merged
martinfleis merged 3 commits intomainfrom
global-pred
Jan 6, 2026
Merged

ENH: implement fusion with the global model in prediction#54
martinfleis merged 3 commits intomainfrom
global-pred

Conversation

@martinfleis
Copy link
Member

Closes #42

Still missing tests and user guide update but this concludes the prediction functionality I wanted to have in.

@martinfleis martinfleis mentioned this pull request Jan 6, 2026
3 tasks
@codecov
Copy link

codecov bot commented Jan 6, 2026

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 86.45%. Comparing base (25533e1) to head (85207f6).
⚠️ Report is 1 commits behind head on main.

Additional details and impacted files
@@            Coverage Diff             @@
##             main      #54      +/-   ##
==========================================
+ Coverage   86.17%   86.45%   +0.28%     
==========================================
  Files           6        6              
  Lines         752      768      +16     
==========================================
+ Hits          648      664      +16     
  Misses        104      104              

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

🚀 New features to boost your workflow:
  • ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

@martinfleis martinfleis changed the title ENH: implement fustion with the global model in prediction ENH: implement fusion with the global model in prediction Jan 6, 2026
@martinfleis martinfleis marked this pull request as ready for review January 6, 2026 19:19
@martinfleis martinfleis requested a review from Copilot January 6, 2026 19:19
Copy link
Contributor

Copilot AI left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Pull request overview

This PR implements fusion between local and global model predictions by adding a global_model_weight parameter to prediction methods. The implementation allows weighted averaging of local and global predictions, following the approach from Georganos et al. (2021).

Key Changes:

  • Added global_model_weight parameter to predict_proba() and predict() methods
  • Implemented weighted averaging between local and global predictions
  • Added test coverage for both classifiers and regressors
  • Updated documentation with examples and added references

Reviewed changes

Copilot reviewed 7 out of 8 changed files in this pull request and generated no comments.

Show a summary per file
File Description
gwlearn/base.py Core implementation of fusion logic in prediction methods
gwlearn/tests/test_base.py Added tests for global weight fusion functionality
docs/source/predict.ipynb Updated documentation with fusion examples
docs/source/references.rst New references page
docs/source/_static/references.bib Added Georganos et al. citation
docs/source/introduction.ipynb Fixed typo ("furhter" → "further")
docs/source/index.md Added references to toctree
docs/source/conf.py Added bibtex reference style configuration

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

@martinfleis martinfleis merged commit d41eccb into main Jan 6, 2026
20 checks passed
@martinfleis martinfleis deleted the global-pred branch January 6, 2026 19:33
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.

Flexibility of prediction

1 participant