Add input validation to _basePCA.inverse_transform #29310
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jeremiedbb
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Jul 25, 2025
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jeremiedbb
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Thanks for the PR @icfaust.
I simplified the validation to only rely on check_array, which deals with empty input.
If the number of components doesn't match, the following operations will fail. With a not as informative error message though, but good enough. I agree that we could have better error messages in that case, but we need to think about it for all estimators, so I leave that for a future issue/PR.
LGTM.
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@jeremiedbb hey thanks for getting it ready to go! |
lucyleeow
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Aug 22, 2025
…29310) Co-authored-by: Jérémie du Boisberranger <[email protected]>
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This PR does input checking for PCA's inverse_transform method. If the input array doesn't have the proper number of components, and generic numpy/array_api error is thrown for the dot product for mismatched indices. A check_is_fitted is also added (as is necessary). After this addition, the extracts the necessary checks from self._validate_data, and applies them for the components instead of the features. The check for array namespace is expanded to follow the convention in PCA.transform.
Have added a supporting test.