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API deprecate default of min_samples for RANSACRegressor
#19390
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…other than LinearRegression and a value is not provided for min_samples. Update docstring to reflect this change.
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So it seems that we have a lot of test that are raising an error now. Please add an entry to the change log at |
I am unsure of how the tests should be fixed. I would be grateful if anyone could show me how. |
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They are tests for which we pass another estimator than |
Co-authored-by: Guillaume Lemaitre <[email protected]>
# Conflicts: # sklearn/linear_model/tests/test_ransac.py
glemaitre
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Some details to improve the PR.
Co-authored-by: Guillaume Lemaitre <[email protected]>
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LGTM
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Hi @hongshaoyang , thank you for your patience and your work so far! Waiting for a second approval, do you mind synchronize with upstream? The continuous integration workflow has been updated for version 1.0 and we need all the checks to be rerun before merging. Thanks! |
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Updated from upstream |
min_samples for RANSACRegressor
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LGTM, thanks @hongshaoyang!
Co-authored-by: Julien Jerphanion <[email protected]>
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Maybe @amueller could have a look since he participated in the discussion on the issue? |
Co-authored-by: Thomas J. Fan <[email protected]>
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Thanks @thomasjpfan I applied the changes. |
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LGTM
API deprecate default of `min_samples` for `RANSACRegressor` (scikit-learn#19390)
…learn#19390) Co-authored-by: Michael Sloma <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]>
Reference Issues/PRs
Closes #6437
Takes over stalled PR and closes #7716
What does this implement/fix? Explain your changes.
By default, RANSACRegressor uses a sample size based on the number of features in the input, which is appropriate for linear regression (which is used by default) but not for other models. This patch raises a ValueError if a model is used other than linear regression and no sample size is provided.
Any other comments?
There are many failing checks from test_estimators due to the raised ValueError - if anyone can point me to a suitable place to update the checks I would be very grateful