ENH Adds feature_names_out to impute module #21078
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sklearn/impute/_base.py
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| Transformed feature names. | ||
| """ | ||
| input_features = _check_feature_names_in(self, input_features) | ||
| return input_features[self.features_] |
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What is our rule for when to prefix and when not? The indicator output column of SimpleImputer is prefixed with "indicator_".
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I do not think we have a rule. I went with SimpleImputer prefixing "indicator_" because it needed to distinguish between the imputed features and the indicator.
Looking at this again, I think we can go with MissingIndcator to add the prefix. This way SimpleImputer only needs to combine them.
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I also think this is fine to preserve the original names for the imputed features.
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Before merging, should we wait for #21334 and then also use |
I do not think we need to wait. This PR is slightly different. |
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FYI: This PR has been merged into the
Took me quite a while to figure that out. |
It is still not included 1.0.2. Should it be this way? |
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@ademyanchuk Yes, it should be this way. I believe scikit-learn follows the process of semantic versioning:
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Thank you, @timotk |
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As info: Scikit-learn does not follow SemVer. But new features as this one, are usually rolled out in a minor version like 1.1.0 or 1.2.0. Bugfix versions like 1.0.1 are for bugfixes only. |
Reference Issues/PRs
Continues #18444
Fixes #21200
What does this implement/fix? Explain your changes.
Adds
feature_names_outto theimputemodule.Any other comments?
There is an edge case I am concerned about:
For this edge case, we can add
sklearnto the prefix resulting insklearn_indicator_a?