[MRG] MNT Removed deprecated attributes and parameters #15803
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Should be ready @amueller @thomasjpfan @glemaitre maybe? |
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I know this is exciting :D but should we wait a bit for the patch releases to minimize potential merge conflicts? |
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merge conflicts with what? |
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with PRs which we'll have to backport to 0.22.X |
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Since these are mostly removals I would say the risk of conflict is minimal, but I've no problem with waiting if you'd rather do that |
sklearn/linear_model/_huber.py
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| @@ -205,7 +205,7 @@ class HuberRegressor(LinearModel, RegressorMixin, BaseEstimator): | |||
| >>> y[:4] = rng.uniform(10, 20, 4) | |||
| >>> huber = HuberRegressor().fit(X, y) | |||
| >>> huber.score(X, y) | |||
| -7.284608623514573 | |||
| -7.284608623514572 | |||
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Why this change? Maybe we are better using an ellipsis?
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I'm not really sure honestly. I double checked and couldn't find a change that could have caused this. It was only failing on a specific platform (MacOS I think), so I don't think it's related to the changes. I'll use ellipsis
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LGTM
Regarding the patch release, I don't think that we will have any issue with we are cherry-picking. As @NicolasHug, we remove stuff so we should not have conflict.
| dtype=[np.float64, np.float32], | ||
| accept_sparse=True, | ||
| warn_on_dtype=True, | ||
| estimator='SomeEstimator') | ||
| assert X_checked.dtype == np.float64 |
| DataConversionWarning, 'KNeighborsClassifier', | ||
| check_X_y, X, y, dtype=np.float64, accept_sparse=True, | ||
| warn_on_dtype=True, estimator=KNeighborsClassifier()) | ||
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| assert X_checked.dtype == np.float64 |
Another batch of deprecation removals
multioutputparameter value inBaseEstimator.scorecall tor2_score