TST add balance property check for linear models #22892
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@rth @agramfort @TomDLT might be interested. |
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I'm not sure where the best place for such a test is. Other models like trees and isotonic regression (should) also fulfil this property and pass such a test. |
TomDLT
approved these changes
Oct 11, 2022
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LGTM
Failing tests:
- For SGDRegressor, it is expected that the algorithm does not fully converge to a high-precision solution. It is due to the stochastic nature of the SGD algorithm, I would just skip the test.
- For SAG/SAGA, it is a bug, which is due to the fact that the random-sample selection does not take into account the sample weights. To fix the bug, we should implement an importance sampling scheme (see LogisticRegression with SAGA using sample_weight does not converge #21305).
jjerphan
approved these changes
Nov 18, 2022
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LGTM. Thank you for adding this theoretical assertion, @lorentzenchr!
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Reference Issues/PRs
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What does this implement/fix? Explain your changes.
This adds a test for all suitable models in
sklearn.linear_modelthat the balance property holds when fit withfit_intercept=True:sum(predicted) = sum(observed)on the training data.Any other comments?
Placed in
linear_model.test.test_common.py.Failing tests are marked as
xfail.