FIX ensure consistency or column and feature names in FunctionTransformer #27801
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glemaitre
commented
Nov 17, 2023
| feature_names_out=feature_names_out, validate=validate | ||
| ) | ||
| transformer.fit_transform(X) | ||
| transformer.fit(X) |
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Calling transform allows us to find the issue with the number of columns and the function used here. Therefore, we can call fit to avoid this check.
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So here, we only raise a better error message. There is no magic but we provide an explanation what to do. I am not a big fan of the magical solution and I am not sure that we will be able to somehow return the expected type (NumPy vs. Pandas) since it will depend of what |
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Needs sync with main before merging. |
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Thanks @lesteve for syncing the PR. Merging with the 2 above approvals. |
This was referenced Jan 23, 2024
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closes #27695
Raise an explicit error when the column names of the container given by
transformis not consistent with the output ofget_feature_names_outinFunctionTransformer.In #27695, the error raised is not easy to understand when the
FunctionTransformeris embedded within aPipeline.Here, we also give some solution how to resolve the problem.
I see that we have test failing in our test suite. I need to check if they are legitimate. I see that some come from the fact that
feature_names_outreturn less names than the number of columns inX_trans.