Comments (1)
The problem is not with Ridge
which always behaves as expected on both machines but rather that LinearRegression
does not always fail as we expect it to fail depending on the machines.
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Related Issues (20)
- Warnings during jupyter-book build
- Averaging Ridge's `alpha` over the CV folds
- Revisit the bagging video
- Optimal pipeline in Exercise M3.02 does not depend on preprocessing strategy
- Correct statement about repeated samples in bootstrap
- How to cite this course/repo? HOT 6
- Add Adult Census dataset description HOT 2
- The thebe integration ("Run code") does not work HOT 3
- slides-ci workflow failure HOT 3
- Investigate moving to Retrolab (JupyterLab with classic notebook interface) rather than Jupyter notebook HOT 2
- Make references to scikit-learn examples more visible HOT 1
- Reenable thebe integration
- [FEATURE REQUEST] Add CC-BY license to footer HOT 3
- Rework lectures ordering in linear models module
- Non linear feature engineering for logistic regression HOT 1
- Use jupyterlab-myst HOT 3
- Add GridSearchCV + train-test split figure in first GridSearchCV notebook
- Copyright remark from 2022 HOT 3
- Revisit the boosting video
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