Fix do not recommend to increase max_iter in ConvergenceWarning when not appropriate#31316
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jeremiedbb merged 6 commits intoMay 12, 2025
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ogrisel
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For information, I requested a copilot review on this PR to assess its usefulness. |
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Pull Request Overview
This PR fixes an issue where the convergence warning for the lbfgs solver was misleading by suggesting that users increase the number of iterations even when it isn’t appropriate. The changes update the warning message in _check_optimize_result, update caller invocations in the GLM and newton solver modules, and adjust the corresponding tests to validate the new behavior.
Reviewed Changes
Copilot reviewed 5 out of 6 changed files in this pull request and generated 2 comments.
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| File | Description |
|---|---|
| sklearn/utils/tests/test_optimize.py | Added tests for the updated convergence warning behavior. |
| sklearn/utils/optimize.py | Modified warning message construction based on the max_iter parameter. |
| sklearn/linear_model/tests/test_logistic.py | Updated the expected warning message format in tests. |
| sklearn/linear_model/_glm/glm.py | Passed the max_iter parameter to _check_optimize_result. |
| sklearn/linear_model/_glm/_newton_solver.py | Adjusted the computed max_iter in fallback_lbfgs_solve and its use in _check_optimize_result. |
Files not reviewed (1)
- doc/whats_new/upcoming_changes/changed-models/31316.fix.rst: Language not supported
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
thomasjpfan
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Minor nit, otherwise LGTM
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
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…hen not appropriate (scikit-learn#31316) Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
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…hen not appropriate (#31316) Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
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While investigating #31164 I found out that
_check_optimize_resultcan sometimes lead to misleading error messages.This fix should help avoid pointing people in a misleading direction when investigating such convergence problems.